Resolving the Price Volatility Puzzle: The Role of...

33
Resolving the Price Volatility Puzzle: The Role of Earnings Gil Sadka First version: November 23, 2003 This version: January 26, 2005 Abstract In an ecient market, prices should vary only if investors change their expectations about cash ows, discount factors, or both. Previous research showed that the dividend yield varies mostly due to variation in expected returns, and contains little information about cash ows. This literature uses dividend growth variation as its measure of cash-ow information. However, according to Miller and Modigliani (1961) with no taxes, given earnings, dividends are strictly a nancing decision and should not aect prices. Consistent with the dividend-policy irrelevance hypothesis, this paper shows that variation in expected protability growth explains as much as 70% of the variation in the dividend yield. Thus, the dividend yield contains information about cash ows in terms of earnings, not dividends. In addition, this paper nds evidence consistent with a permanent downward shift in the dividend yield in the 1990s. Controlling for this permanent shift, the results indicate that the dividend yield has not lost its ability to predict returns. Keywords: accounting valuation, expected-return variation, protability, equity premium, variance decomposition I would like to thank Ray Ball, Philip Berger, John Cochrane, Richard Leftwich, Efraim Sadka, Ronnie Sadka, Wendy Rothschild, Douglas Skinner, Kendrew Witt, and the workshop participants at the University of Chicago for comments and suggestions. Any errors are my own. I gratefully acknowledge nancial support from the University of Chicago, Graduate School of Business. University of Chicago Graduate School of Business, 5807 S. Woodlawn Ave., Chicago, Illinois 60637; e-mail: [email protected].

Transcript of Resolving the Price Volatility Puzzle: The Role of...

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Resolving the Price Volatility Puzzle The Role of Earningslowast

Gil Sadkadagger

First version November 23 2003

This version January 26 2005

Abstract

In an efficient market prices should vary only if investors change their expectations about

cash flows discount factors or both Previous research showed that the dividend yield varies

mostly due to variation in expected returns and contains little information about cash flows

This literature uses dividend growth variation as its measure of cash-flow information However

according to Miller and Modigliani (1961) with no taxes given earnings dividends are strictly a

financing decision and should not affect prices Consistent with the dividend-policy irrelevance

hypothesis this paper shows that variation in expected profitability growth explains as much

as 70 of the variation in the dividend yield Thus the dividend yield contains information

about cash flows in terms of earnings not dividends In addition this paper finds evidence

consistent with a permanent downward shift in the dividend yield in the 1990s Controlling

for this permanent shift the results indicate that the dividend yield has not lost its ability to

predict returns

Keywords accounting valuation expected-return variation profitability equity premium variance

decomposition

lowastI would like to thank Ray Ball Philip Berger John Cochrane Richard Leftwich Efraim Sadka Ronnie Sadka

Wendy Rothschild Douglas Skinner Kendrew Witt and the workshop participants at the University of Chicago for

comments and suggestions Any errors are my own I gratefully acknowledge financial support from the University

of Chicago Graduate School of BusinessdaggerUniversity of Chicago Graduate School of Business 5807 S Woodlawn Ave Chicago Illinois 60637 e-mail

gsadkaChicagoGSBedu

1 Introduction

In general prices are expected discounted cash flows Thus there are two factors that may af-

fect prices the expectations regarding discount factors and expectations regarding future cash

flows Research on stock price volatility has found that variation in expected returns explains

most of the variation in aggregate stock returns (the market portfolio) and the dividend yield (eg

Campbell and Shiller (1988a 1988b) Campbell (1991) and Campbell and Ammer (1993))1 On

the other hand variation in expected dividends does not explain much of the variation in prices

Consistent with this analysis on stock price volatility the finance literature has found that re-

turns are predictable and dividends are not (see eg Fama and French (1988 1989) Keim and

Stambaugh (1986) Lettau and Ludvigson (2001) Kothari and Shanken (1997) Lamont (1998)

and Cochrane (2001)) Exceptions are Ribeiro (2002) and Lettau and Ludvigson (2004) who find

that the labor-income-to-dividend and the consumption-to-wealth ratios identify some predictable

dividend variation While these recent studies find evidence of dividend predictability it remains

the case that dividends do not seem to affect the dividend-price ratio (dividend yield)

These results are somewhat disturbing Prices are simply expected discounted cash flows Thus

one would expect that both cash flow and return variation would generate price variation Since

the dividend yield is stationary and varies it must predict either returns or cash flows or both

The evidence described above suggests that only expected returns variation affects the aggregate

dividend yield For instance as Cochrane (2001) points out It is nonetheless an uncomfortable

fact that almost all variation in pricedividend ratios is due to variation in expected excess returns

How nice it would be if high prices reflected expectations of higher future cash flows

This literature focuses on dividends as cash flow information However dividends are not

expected to have an effect on prices According to Miller and Modigliani (1961) given earnings and

ignoring taxes dividend policy is irrelevant and should not affect prices Dividends are irrelevant

because earnings measure the potential cash flow that the asset generates and dividends are only

an endogenous financing decision made by the firm and its stock holders (when the dividend is

1When the analysis is applied in the cross-section (eg Vuolteenaho (2002) Callen and Segal (2004) Easton (2004)

and Cohen Polk and Vuolteenaho (2003)) the results suggest that variation in expected profitability can explain

much of the variation in the firm-level book-to-market returns and earnings-price ratios The difference between the

aggregate and firm-level results has been attributed in part to the relative strength of the idiosyncratic components

of cash flow variation versus the systematic components of expected returns

2

distributed) Earnings on the other hand are not an endogenous decision they are a result of the

firmsrsquo operations and investments and thus represent the ability of firms to distribute dividends

The difference between dividends and earnings approximates the difference between actual cash

flow and free cash flow Investors are not interested in expected short-term dividends They are

interested in the expected ability to pay out cash ie free cash flow Therefore the relevant

variable to predict or in other words the variable that should be reflected in prices is profitability

growth and not dividend growth

The primary advantage of using accounting income in this setting as opposed to dividends

stems from the theory developed by Miller and Modigliani (1961) The theory suggests that given

earnings and ignoring taxes dividend policy is irrelevant This paper does not claim that dividends

do not matter In the long-run investors are concerned with discounted cash flows (dividends) that

the asset produces However this paper suggests that on the aggregate level short-run dividend

variations do not affect prices On the other hand investors will be sensitive to earnings variations

because they provide information about the long-run dividend flow Accounting income must be

received in cash or assets in the future which will eventually be distributed as dividends In

contrast dividends do not necessarily reflect future cash flows they are distributed from past and

current earnings

The hypothesis of short-term dividend irrelevance is apparent in stock prices particularly in

the 1990s There are many firms trading with a positive price that do not pay dividends and

are not expected to pay dividends in the short-run Even though these firms may not distribute

dividends or are not expected to in the short-term it does not mean their prices do not vary due

to changes in expected cash flows The price of the stock reflects the long-run dividend stream

which is a function of current and expected earnings - dividends follow earnings The firm invests

it accrues earnings the earnings turn into cash flows and when the firm no longer requires the cash

to finance its operations it distributes it as dividends In sum in the long-run it does not matter

if we choose dividends or earnings because they are the same but earnings are more appropriate

in short-horizon tests of stock price volatility

This role of accounting information has been studied extensively in the literature For example

Dechow (1994) illustrates that accounting earnings and accruals are better measures of firmsrsquo

performance than cash flows2 A common example is accounts receivables Assume that some of2See also Basu (1997) Ball Kothari and Robin (2000) Dechow Kothari and Watts (1998) and Callen and Segal

3

the firmrsquos sales are made on account In this case the firm and its assets generate the right to receive

cash flows Because the cash is not yet received then in order to measure the firmrsquos performance and

the cash flows itrsquos entitled to one must include accounts receivables in the performance measure

Therefore cash measures alone would not be appropriate as performance measures

Earnings have several advantages over dividends in addition to the fact that dividends are a

result of financing decisions The legal status of earnings makes it the most appropriate measure of

future cash flows Firms distribute dividends from accrued earnings Legally earnings represent the

firmrsquos verifiable cash flows generated by its investments and assets that belong to its stock holders

While dividends might provide a signal for future profitability (eg Watts (1973) and Healy and

Palepu (1988) and Nissim and Ziv (2001))3 it remains the case that dividends are distributed from

accrued earnings They cannot legally exceed the book value of retained earnings

Previous research provides an additional reason for using earnings as a proxy for future cash

flows Previous literature found that prices contain information about expected earnings For

instance empirical evidence suggests that prices predict earnings better than conventional time

series models and that current price changes reflect future expected earnings shocks (see eg Beaver

Clarke and Wright (1979) Beaver Lambert and Morse (1980) Collins Kothari and Rayburn

(1987) Collins and Kothari (1989) and Kothari and Sloan (1992)) This result is also apparent in

early research such as Ball and Brown (1968) The accounting literature on prices and earnings

implies that the slope on the dividend yield with respect to earnings growth is expected to be

negative That is higher prices reflect expectations for higher future profitability Therefore

higher expected earnings push prices up and the dividend yield down

The third reason for using the aggregate earnings and earnings-dividend ratio in tests of price

volatility is the evidence concerning their predictability For instance Lamont (1998) finds that the

dividend-earnings ratio co-integrates with the dividend-price ratio and predicts returns4 Notice

that earnings growth multiplied by the dividend-earnings ratio growth is equal to dividend growth

The above implies that earnings and the earning-dividend ratio are good candidates to test for

(2004)3 In contrast DeAngelo DeAngelo and Skinner (1996) find that dividends are not a reliable signal for profitability

In addition Watts (1973) finds only weak evidence of the predictive power of dividends with respect to earnings4Vuolteenaho (2000) finds that as much as 40 of the variation in the aggregate book-to-market ratio is due to

expected profitability (Return on Equity - ROE)

4

the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and

Brown (1967)) that is priced

Based on the discussion above this paper contributes to the study of price volatility and pre-

dictability of earnings and returns by studying the information contained in the aggregate dividend

yield with regard to cash flows Specifically this paper investigates whether the dividend yield

contains information about future cash flows in terms of accounting income The results show that

expected profitability is a major source of dividend yield variation During the sample period (1952

- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield

Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield

This finding is consistent with a large body of research that studies the role of accounting income

in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball

Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings

and accruals are more strongly associated with stock prices than are dividends and cash flows

In the short-term the dividend yield is informative about earnings not dividends In the long-

term over the life of the firm earnings and dividends are the same But in the short-term such as

the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate

measure of cash flows because earnings are more timely In fact the results suggest that the

dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to

expected dividend smoothing when expected earnings are high the expected dividend-earnings

ratio is low and vice versaUsing these results this paper shows that the dividend yield would

only be able to predict dividends in the very long-term Higher expected earnings are not expected

to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope

coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-

term earnings rather than dividends is the more appropriate and more useful measure of cash

flows

As discussed above this paper finds that the dividend yield predicts both expected returns and

expected earnings growth Since the dividend yield predicts both returns and profitability it is

clear that the two are not independent In fact the results indicate a negative contemporaneous

correlation between returns and earnings growth However returns are positively correlated (021)

5See also Ribeiro (2002) and Pastor and Veronesi (2003)

5

with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower

dividend yield predicts both low expected returns and high earnings growth the contemporaneous

correlation between earnings growth and returns is expected to be negative A sharp price increase

(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence

should be positively correlated with long-term earnings growth Consequently variations in the

dividend yield due to variations in expected returns can be attributable in part to variations in

expected earnings

In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson

(2004)) find that the dividend yield has declined and lost its ability to predict returns This

paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the

permanent change the results suggest that the dividend yield is a good predictor of future excess

returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon

returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported

in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the

dividend yield

The remainder of this paper is organized as follows Section 2 provides a short description of

the data and their sources Section 3 tests whether the dividend yield contains information about

cash flows through expected accounting earnings growth Section 4 includes some additional tests

including tests aimed at determining whether the equilibrium dividend yield has declined Section

5 concludes

2 Data

The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases

for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end

requirement avoids temporal misspecifications due to different reporting and different cumulation

periods of annual earnings The returns dividends and price data are extracted from the CRSP

monthly data set The earnings item used is the earnings before extraordinary items in COMPU-

STAT The annual financial variables are measured from April of year t until March of year t+ 1

Table 1 reports summary statistics for the data used in this paper The table reports the time

series averages medians and standard deviations of the variables used in the paper The annual

6

returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is

extracted from the Fama and French three factor model data in the WRDS database

The earnings growth measure is defined as growth in the sum of annual earnings for the sample

firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)

in its measure of profitability for two reasons First accounting conservatism7 requires timely

recognition of expected declines in cash flows and at the same time does not allow firms to recognize

unverifiable expected increases in cash flows This asymmetry in recognition of economic income

results in a skewed earnings distribution (with relatively large negative values) This skewness is

likely to affect profitability measures such as average profitability growth and average return on

equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric

distribution Second earnings growth is very similar in essence to dividend growth commonly used

in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the

profitability of the market portfolio which is the variable of interest

3 The Dividend Yield and the Predictability of Earnings Divi-

dends and Returns

Previous studies suggest that the dividend yield varies mainly due to variations in expected returns

As noted above the stationarity of the dividend yield implies that it must predict either returns

or cash flows or both The evidence suggests that the dividend-price ratio contains very little

information regarding future dividend growth

Table 2 reports the estimation of the regression models

Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)

and

Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)

The table provides a short summary of previously recorded results in the literature (eg Fama and

6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)

7

French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the

long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very

similar to the results reported in Fama and French (1988) The coefficient on the dividend-price

ratio increases with horizon as well

The relation between short and long-term predictability can be interpreted by the following two

assumptions

Rt+1 = a middotDPt + ε1t+1 (3)

and

DPt+1 = ρ middotDPt + ε2t+1 (4)

Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the

coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are

all positive implying that low prices are associated with high expected returns

While the dividend-price ratio predicts returns it does not predict future dividend growth The

coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes

for different horizons Moreover the adjusted R2 for all horizons is negative

31 Predictability of Earnings

To summarize up to this point the dividend yield predicts returns but not dividend growth This

lack of dividend predictability led the finance literature to conclude that expected returns are the

main cause for aggregate price movements Although the dividend-price ratio does not predict

dividend growth it may contain information about expected cash flow through other measures

such as accounting earnings In fact as discussed above investors should be more interested in

measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends

which represent financing decisions

To test whether the dividend yield predicts earnings growth the following two regression models

were estimated for 1-10 year horizons

8

Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)

and

EtDt

Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)

Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot

[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed

as information about expected earnings growth and information about the expected earnings-

dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth

can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use

of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of

cash flows

The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains

information about cash flows in terms of earnings The dividend yield seems to be predicting long-

term earnings growth especially at the 6-year horizon and longer This result is consistent with the

conservative nature of accounting Economic gains are not recorded in a timely fashion Economic

growth at period t would result in earnings increases as much as ten years later The patterns of

predictability are similar to those of the returns predictability reported in Table 2 The coefficient

on the dividend yield increases in absolute value with the horizon as does the R2

The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend

smoothing While the dividend yield predicts future earnings growth it also predicts changes in

the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-

term and it offsets the effects of expected earnings growth The results suggest that an increase in

expected profitability is associated with an expected decline in the dividend-earnings ratio In other

words dividends do not vary as strongly as earnings and an expected earnings increase does not

8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change

qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and

Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean

surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value

or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation

9

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

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Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

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Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 2: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

1 Introduction

In general prices are expected discounted cash flows Thus there are two factors that may af-

fect prices the expectations regarding discount factors and expectations regarding future cash

flows Research on stock price volatility has found that variation in expected returns explains

most of the variation in aggregate stock returns (the market portfolio) and the dividend yield (eg

Campbell and Shiller (1988a 1988b) Campbell (1991) and Campbell and Ammer (1993))1 On

the other hand variation in expected dividends does not explain much of the variation in prices

Consistent with this analysis on stock price volatility the finance literature has found that re-

turns are predictable and dividends are not (see eg Fama and French (1988 1989) Keim and

Stambaugh (1986) Lettau and Ludvigson (2001) Kothari and Shanken (1997) Lamont (1998)

and Cochrane (2001)) Exceptions are Ribeiro (2002) and Lettau and Ludvigson (2004) who find

that the labor-income-to-dividend and the consumption-to-wealth ratios identify some predictable

dividend variation While these recent studies find evidence of dividend predictability it remains

the case that dividends do not seem to affect the dividend-price ratio (dividend yield)

These results are somewhat disturbing Prices are simply expected discounted cash flows Thus

one would expect that both cash flow and return variation would generate price variation Since

the dividend yield is stationary and varies it must predict either returns or cash flows or both

The evidence described above suggests that only expected returns variation affects the aggregate

dividend yield For instance as Cochrane (2001) points out It is nonetheless an uncomfortable

fact that almost all variation in pricedividend ratios is due to variation in expected excess returns

How nice it would be if high prices reflected expectations of higher future cash flows

This literature focuses on dividends as cash flow information However dividends are not

expected to have an effect on prices According to Miller and Modigliani (1961) given earnings and

ignoring taxes dividend policy is irrelevant and should not affect prices Dividends are irrelevant

because earnings measure the potential cash flow that the asset generates and dividends are only

an endogenous financing decision made by the firm and its stock holders (when the dividend is

1When the analysis is applied in the cross-section (eg Vuolteenaho (2002) Callen and Segal (2004) Easton (2004)

and Cohen Polk and Vuolteenaho (2003)) the results suggest that variation in expected profitability can explain

much of the variation in the firm-level book-to-market returns and earnings-price ratios The difference between the

aggregate and firm-level results has been attributed in part to the relative strength of the idiosyncratic components

of cash flow variation versus the systematic components of expected returns

2

distributed) Earnings on the other hand are not an endogenous decision they are a result of the

firmsrsquo operations and investments and thus represent the ability of firms to distribute dividends

The difference between dividends and earnings approximates the difference between actual cash

flow and free cash flow Investors are not interested in expected short-term dividends They are

interested in the expected ability to pay out cash ie free cash flow Therefore the relevant

variable to predict or in other words the variable that should be reflected in prices is profitability

growth and not dividend growth

The primary advantage of using accounting income in this setting as opposed to dividends

stems from the theory developed by Miller and Modigliani (1961) The theory suggests that given

earnings and ignoring taxes dividend policy is irrelevant This paper does not claim that dividends

do not matter In the long-run investors are concerned with discounted cash flows (dividends) that

the asset produces However this paper suggests that on the aggregate level short-run dividend

variations do not affect prices On the other hand investors will be sensitive to earnings variations

because they provide information about the long-run dividend flow Accounting income must be

received in cash or assets in the future which will eventually be distributed as dividends In

contrast dividends do not necessarily reflect future cash flows they are distributed from past and

current earnings

The hypothesis of short-term dividend irrelevance is apparent in stock prices particularly in

the 1990s There are many firms trading with a positive price that do not pay dividends and

are not expected to pay dividends in the short-run Even though these firms may not distribute

dividends or are not expected to in the short-term it does not mean their prices do not vary due

to changes in expected cash flows The price of the stock reflects the long-run dividend stream

which is a function of current and expected earnings - dividends follow earnings The firm invests

it accrues earnings the earnings turn into cash flows and when the firm no longer requires the cash

to finance its operations it distributes it as dividends In sum in the long-run it does not matter

if we choose dividends or earnings because they are the same but earnings are more appropriate

in short-horizon tests of stock price volatility

This role of accounting information has been studied extensively in the literature For example

Dechow (1994) illustrates that accounting earnings and accruals are better measures of firmsrsquo

performance than cash flows2 A common example is accounts receivables Assume that some of2See also Basu (1997) Ball Kothari and Robin (2000) Dechow Kothari and Watts (1998) and Callen and Segal

3

the firmrsquos sales are made on account In this case the firm and its assets generate the right to receive

cash flows Because the cash is not yet received then in order to measure the firmrsquos performance and

the cash flows itrsquos entitled to one must include accounts receivables in the performance measure

Therefore cash measures alone would not be appropriate as performance measures

Earnings have several advantages over dividends in addition to the fact that dividends are a

result of financing decisions The legal status of earnings makes it the most appropriate measure of

future cash flows Firms distribute dividends from accrued earnings Legally earnings represent the

firmrsquos verifiable cash flows generated by its investments and assets that belong to its stock holders

While dividends might provide a signal for future profitability (eg Watts (1973) and Healy and

Palepu (1988) and Nissim and Ziv (2001))3 it remains the case that dividends are distributed from

accrued earnings They cannot legally exceed the book value of retained earnings

Previous research provides an additional reason for using earnings as a proxy for future cash

flows Previous literature found that prices contain information about expected earnings For

instance empirical evidence suggests that prices predict earnings better than conventional time

series models and that current price changes reflect future expected earnings shocks (see eg Beaver

Clarke and Wright (1979) Beaver Lambert and Morse (1980) Collins Kothari and Rayburn

(1987) Collins and Kothari (1989) and Kothari and Sloan (1992)) This result is also apparent in

early research such as Ball and Brown (1968) The accounting literature on prices and earnings

implies that the slope on the dividend yield with respect to earnings growth is expected to be

negative That is higher prices reflect expectations for higher future profitability Therefore

higher expected earnings push prices up and the dividend yield down

The third reason for using the aggregate earnings and earnings-dividend ratio in tests of price

volatility is the evidence concerning their predictability For instance Lamont (1998) finds that the

dividend-earnings ratio co-integrates with the dividend-price ratio and predicts returns4 Notice

that earnings growth multiplied by the dividend-earnings ratio growth is equal to dividend growth

The above implies that earnings and the earning-dividend ratio are good candidates to test for

(2004)3 In contrast DeAngelo DeAngelo and Skinner (1996) find that dividends are not a reliable signal for profitability

In addition Watts (1973) finds only weak evidence of the predictive power of dividends with respect to earnings4Vuolteenaho (2000) finds that as much as 40 of the variation in the aggregate book-to-market ratio is due to

expected profitability (Return on Equity - ROE)

4

the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and

Brown (1967)) that is priced

Based on the discussion above this paper contributes to the study of price volatility and pre-

dictability of earnings and returns by studying the information contained in the aggregate dividend

yield with regard to cash flows Specifically this paper investigates whether the dividend yield

contains information about future cash flows in terms of accounting income The results show that

expected profitability is a major source of dividend yield variation During the sample period (1952

- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield

Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield

This finding is consistent with a large body of research that studies the role of accounting income

in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball

Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings

and accruals are more strongly associated with stock prices than are dividends and cash flows

In the short-term the dividend yield is informative about earnings not dividends In the long-

term over the life of the firm earnings and dividends are the same But in the short-term such as

the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate

measure of cash flows because earnings are more timely In fact the results suggest that the

dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to

expected dividend smoothing when expected earnings are high the expected dividend-earnings

ratio is low and vice versaUsing these results this paper shows that the dividend yield would

only be able to predict dividends in the very long-term Higher expected earnings are not expected

to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope

coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-

term earnings rather than dividends is the more appropriate and more useful measure of cash

flows

As discussed above this paper finds that the dividend yield predicts both expected returns and

expected earnings growth Since the dividend yield predicts both returns and profitability it is

clear that the two are not independent In fact the results indicate a negative contemporaneous

correlation between returns and earnings growth However returns are positively correlated (021)

5See also Ribeiro (2002) and Pastor and Veronesi (2003)

5

with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower

dividend yield predicts both low expected returns and high earnings growth the contemporaneous

correlation between earnings growth and returns is expected to be negative A sharp price increase

(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence

should be positively correlated with long-term earnings growth Consequently variations in the

dividend yield due to variations in expected returns can be attributable in part to variations in

expected earnings

In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson

(2004)) find that the dividend yield has declined and lost its ability to predict returns This

paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the

permanent change the results suggest that the dividend yield is a good predictor of future excess

returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon

returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported

in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the

dividend yield

The remainder of this paper is organized as follows Section 2 provides a short description of

the data and their sources Section 3 tests whether the dividend yield contains information about

cash flows through expected accounting earnings growth Section 4 includes some additional tests

including tests aimed at determining whether the equilibrium dividend yield has declined Section

5 concludes

2 Data

The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases

for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end

requirement avoids temporal misspecifications due to different reporting and different cumulation

periods of annual earnings The returns dividends and price data are extracted from the CRSP

monthly data set The earnings item used is the earnings before extraordinary items in COMPU-

STAT The annual financial variables are measured from April of year t until March of year t+ 1

Table 1 reports summary statistics for the data used in this paper The table reports the time

series averages medians and standard deviations of the variables used in the paper The annual

6

returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is

extracted from the Fama and French three factor model data in the WRDS database

The earnings growth measure is defined as growth in the sum of annual earnings for the sample

firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)

in its measure of profitability for two reasons First accounting conservatism7 requires timely

recognition of expected declines in cash flows and at the same time does not allow firms to recognize

unverifiable expected increases in cash flows This asymmetry in recognition of economic income

results in a skewed earnings distribution (with relatively large negative values) This skewness is

likely to affect profitability measures such as average profitability growth and average return on

equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric

distribution Second earnings growth is very similar in essence to dividend growth commonly used

in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the

profitability of the market portfolio which is the variable of interest

3 The Dividend Yield and the Predictability of Earnings Divi-

dends and Returns

Previous studies suggest that the dividend yield varies mainly due to variations in expected returns

As noted above the stationarity of the dividend yield implies that it must predict either returns

or cash flows or both The evidence suggests that the dividend-price ratio contains very little

information regarding future dividend growth

Table 2 reports the estimation of the regression models

Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)

and

Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)

The table provides a short summary of previously recorded results in the literature (eg Fama and

6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)

7

French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the

long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very

similar to the results reported in Fama and French (1988) The coefficient on the dividend-price

ratio increases with horizon as well

The relation between short and long-term predictability can be interpreted by the following two

assumptions

Rt+1 = a middotDPt + ε1t+1 (3)

and

DPt+1 = ρ middotDPt + ε2t+1 (4)

Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the

coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are

all positive implying that low prices are associated with high expected returns

While the dividend-price ratio predicts returns it does not predict future dividend growth The

coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes

for different horizons Moreover the adjusted R2 for all horizons is negative

31 Predictability of Earnings

To summarize up to this point the dividend yield predicts returns but not dividend growth This

lack of dividend predictability led the finance literature to conclude that expected returns are the

main cause for aggregate price movements Although the dividend-price ratio does not predict

dividend growth it may contain information about expected cash flow through other measures

such as accounting earnings In fact as discussed above investors should be more interested in

measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends

which represent financing decisions

To test whether the dividend yield predicts earnings growth the following two regression models

were estimated for 1-10 year horizons

8

Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)

and

EtDt

Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)

Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot

[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed

as information about expected earnings growth and information about the expected earnings-

dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth

can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use

of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of

cash flows

The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains

information about cash flows in terms of earnings The dividend yield seems to be predicting long-

term earnings growth especially at the 6-year horizon and longer This result is consistent with the

conservative nature of accounting Economic gains are not recorded in a timely fashion Economic

growth at period t would result in earnings increases as much as ten years later The patterns of

predictability are similar to those of the returns predictability reported in Table 2 The coefficient

on the dividend yield increases in absolute value with the horizon as does the R2

The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend

smoothing While the dividend yield predicts future earnings growth it also predicts changes in

the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-

term and it offsets the effects of expected earnings growth The results suggest that an increase in

expected profitability is associated with an expected decline in the dividend-earnings ratio In other

words dividends do not vary as strongly as earnings and an expected earnings increase does not

8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change

qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and

Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean

surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value

or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation

9

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

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Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

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Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

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Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 3: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

distributed) Earnings on the other hand are not an endogenous decision they are a result of the

firmsrsquo operations and investments and thus represent the ability of firms to distribute dividends

The difference between dividends and earnings approximates the difference between actual cash

flow and free cash flow Investors are not interested in expected short-term dividends They are

interested in the expected ability to pay out cash ie free cash flow Therefore the relevant

variable to predict or in other words the variable that should be reflected in prices is profitability

growth and not dividend growth

The primary advantage of using accounting income in this setting as opposed to dividends

stems from the theory developed by Miller and Modigliani (1961) The theory suggests that given

earnings and ignoring taxes dividend policy is irrelevant This paper does not claim that dividends

do not matter In the long-run investors are concerned with discounted cash flows (dividends) that

the asset produces However this paper suggests that on the aggregate level short-run dividend

variations do not affect prices On the other hand investors will be sensitive to earnings variations

because they provide information about the long-run dividend flow Accounting income must be

received in cash or assets in the future which will eventually be distributed as dividends In

contrast dividends do not necessarily reflect future cash flows they are distributed from past and

current earnings

The hypothesis of short-term dividend irrelevance is apparent in stock prices particularly in

the 1990s There are many firms trading with a positive price that do not pay dividends and

are not expected to pay dividends in the short-run Even though these firms may not distribute

dividends or are not expected to in the short-term it does not mean their prices do not vary due

to changes in expected cash flows The price of the stock reflects the long-run dividend stream

which is a function of current and expected earnings - dividends follow earnings The firm invests

it accrues earnings the earnings turn into cash flows and when the firm no longer requires the cash

to finance its operations it distributes it as dividends In sum in the long-run it does not matter

if we choose dividends or earnings because they are the same but earnings are more appropriate

in short-horizon tests of stock price volatility

This role of accounting information has been studied extensively in the literature For example

Dechow (1994) illustrates that accounting earnings and accruals are better measures of firmsrsquo

performance than cash flows2 A common example is accounts receivables Assume that some of2See also Basu (1997) Ball Kothari and Robin (2000) Dechow Kothari and Watts (1998) and Callen and Segal

3

the firmrsquos sales are made on account In this case the firm and its assets generate the right to receive

cash flows Because the cash is not yet received then in order to measure the firmrsquos performance and

the cash flows itrsquos entitled to one must include accounts receivables in the performance measure

Therefore cash measures alone would not be appropriate as performance measures

Earnings have several advantages over dividends in addition to the fact that dividends are a

result of financing decisions The legal status of earnings makes it the most appropriate measure of

future cash flows Firms distribute dividends from accrued earnings Legally earnings represent the

firmrsquos verifiable cash flows generated by its investments and assets that belong to its stock holders

While dividends might provide a signal for future profitability (eg Watts (1973) and Healy and

Palepu (1988) and Nissim and Ziv (2001))3 it remains the case that dividends are distributed from

accrued earnings They cannot legally exceed the book value of retained earnings

Previous research provides an additional reason for using earnings as a proxy for future cash

flows Previous literature found that prices contain information about expected earnings For

instance empirical evidence suggests that prices predict earnings better than conventional time

series models and that current price changes reflect future expected earnings shocks (see eg Beaver

Clarke and Wright (1979) Beaver Lambert and Morse (1980) Collins Kothari and Rayburn

(1987) Collins and Kothari (1989) and Kothari and Sloan (1992)) This result is also apparent in

early research such as Ball and Brown (1968) The accounting literature on prices and earnings

implies that the slope on the dividend yield with respect to earnings growth is expected to be

negative That is higher prices reflect expectations for higher future profitability Therefore

higher expected earnings push prices up and the dividend yield down

The third reason for using the aggregate earnings and earnings-dividend ratio in tests of price

volatility is the evidence concerning their predictability For instance Lamont (1998) finds that the

dividend-earnings ratio co-integrates with the dividend-price ratio and predicts returns4 Notice

that earnings growth multiplied by the dividend-earnings ratio growth is equal to dividend growth

The above implies that earnings and the earning-dividend ratio are good candidates to test for

(2004)3 In contrast DeAngelo DeAngelo and Skinner (1996) find that dividends are not a reliable signal for profitability

In addition Watts (1973) finds only weak evidence of the predictive power of dividends with respect to earnings4Vuolteenaho (2000) finds that as much as 40 of the variation in the aggregate book-to-market ratio is due to

expected profitability (Return on Equity - ROE)

4

the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and

Brown (1967)) that is priced

Based on the discussion above this paper contributes to the study of price volatility and pre-

dictability of earnings and returns by studying the information contained in the aggregate dividend

yield with regard to cash flows Specifically this paper investigates whether the dividend yield

contains information about future cash flows in terms of accounting income The results show that

expected profitability is a major source of dividend yield variation During the sample period (1952

- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield

Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield

This finding is consistent with a large body of research that studies the role of accounting income

in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball

Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings

and accruals are more strongly associated with stock prices than are dividends and cash flows

In the short-term the dividend yield is informative about earnings not dividends In the long-

term over the life of the firm earnings and dividends are the same But in the short-term such as

the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate

measure of cash flows because earnings are more timely In fact the results suggest that the

dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to

expected dividend smoothing when expected earnings are high the expected dividend-earnings

ratio is low and vice versaUsing these results this paper shows that the dividend yield would

only be able to predict dividends in the very long-term Higher expected earnings are not expected

to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope

coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-

term earnings rather than dividends is the more appropriate and more useful measure of cash

flows

As discussed above this paper finds that the dividend yield predicts both expected returns and

expected earnings growth Since the dividend yield predicts both returns and profitability it is

clear that the two are not independent In fact the results indicate a negative contemporaneous

correlation between returns and earnings growth However returns are positively correlated (021)

5See also Ribeiro (2002) and Pastor and Veronesi (2003)

5

with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower

dividend yield predicts both low expected returns and high earnings growth the contemporaneous

correlation between earnings growth and returns is expected to be negative A sharp price increase

(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence

should be positively correlated with long-term earnings growth Consequently variations in the

dividend yield due to variations in expected returns can be attributable in part to variations in

expected earnings

In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson

(2004)) find that the dividend yield has declined and lost its ability to predict returns This

paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the

permanent change the results suggest that the dividend yield is a good predictor of future excess

returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon

returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported

in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the

dividend yield

The remainder of this paper is organized as follows Section 2 provides a short description of

the data and their sources Section 3 tests whether the dividend yield contains information about

cash flows through expected accounting earnings growth Section 4 includes some additional tests

including tests aimed at determining whether the equilibrium dividend yield has declined Section

5 concludes

2 Data

The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases

for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end

requirement avoids temporal misspecifications due to different reporting and different cumulation

periods of annual earnings The returns dividends and price data are extracted from the CRSP

monthly data set The earnings item used is the earnings before extraordinary items in COMPU-

STAT The annual financial variables are measured from April of year t until March of year t+ 1

Table 1 reports summary statistics for the data used in this paper The table reports the time

series averages medians and standard deviations of the variables used in the paper The annual

6

returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is

extracted from the Fama and French three factor model data in the WRDS database

The earnings growth measure is defined as growth in the sum of annual earnings for the sample

firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)

in its measure of profitability for two reasons First accounting conservatism7 requires timely

recognition of expected declines in cash flows and at the same time does not allow firms to recognize

unverifiable expected increases in cash flows This asymmetry in recognition of economic income

results in a skewed earnings distribution (with relatively large negative values) This skewness is

likely to affect profitability measures such as average profitability growth and average return on

equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric

distribution Second earnings growth is very similar in essence to dividend growth commonly used

in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the

profitability of the market portfolio which is the variable of interest

3 The Dividend Yield and the Predictability of Earnings Divi-

dends and Returns

Previous studies suggest that the dividend yield varies mainly due to variations in expected returns

As noted above the stationarity of the dividend yield implies that it must predict either returns

or cash flows or both The evidence suggests that the dividend-price ratio contains very little

information regarding future dividend growth

Table 2 reports the estimation of the regression models

Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)

and

Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)

The table provides a short summary of previously recorded results in the literature (eg Fama and

6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)

7

French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the

long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very

similar to the results reported in Fama and French (1988) The coefficient on the dividend-price

ratio increases with horizon as well

The relation between short and long-term predictability can be interpreted by the following two

assumptions

Rt+1 = a middotDPt + ε1t+1 (3)

and

DPt+1 = ρ middotDPt + ε2t+1 (4)

Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the

coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are

all positive implying that low prices are associated with high expected returns

While the dividend-price ratio predicts returns it does not predict future dividend growth The

coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes

for different horizons Moreover the adjusted R2 for all horizons is negative

31 Predictability of Earnings

To summarize up to this point the dividend yield predicts returns but not dividend growth This

lack of dividend predictability led the finance literature to conclude that expected returns are the

main cause for aggregate price movements Although the dividend-price ratio does not predict

dividend growth it may contain information about expected cash flow through other measures

such as accounting earnings In fact as discussed above investors should be more interested in

measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends

which represent financing decisions

To test whether the dividend yield predicts earnings growth the following two regression models

were estimated for 1-10 year horizons

8

Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)

and

EtDt

Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)

Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot

[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed

as information about expected earnings growth and information about the expected earnings-

dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth

can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use

of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of

cash flows

The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains

information about cash flows in terms of earnings The dividend yield seems to be predicting long-

term earnings growth especially at the 6-year horizon and longer This result is consistent with the

conservative nature of accounting Economic gains are not recorded in a timely fashion Economic

growth at period t would result in earnings increases as much as ten years later The patterns of

predictability are similar to those of the returns predictability reported in Table 2 The coefficient

on the dividend yield increases in absolute value with the horizon as does the R2

The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend

smoothing While the dividend yield predicts future earnings growth it also predicts changes in

the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-

term and it offsets the effects of expected earnings growth The results suggest that an increase in

expected profitability is associated with an expected decline in the dividend-earnings ratio In other

words dividends do not vary as strongly as earnings and an expected earnings increase does not

8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change

qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and

Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean

surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value

or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation

9

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies

5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of

Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of

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prices with respect to earnings Journal of Accounting and Economics 9 111-138DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1992 Dividends and losses Journal of

Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling

and the disappearance of sustained earnings growth Journal of Financial Economics 40 341-371Dechow Patricia 1994 Accounting earnings and cash flows as measures of firm performance Journal

of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on

equity capital The Accounting Review 79 (1) 73-95

21

Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity

Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636

Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 4: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

the firmrsquos sales are made on account In this case the firm and its assets generate the right to receive

cash flows Because the cash is not yet received then in order to measure the firmrsquos performance and

the cash flows itrsquos entitled to one must include accounts receivables in the performance measure

Therefore cash measures alone would not be appropriate as performance measures

Earnings have several advantages over dividends in addition to the fact that dividends are a

result of financing decisions The legal status of earnings makes it the most appropriate measure of

future cash flows Firms distribute dividends from accrued earnings Legally earnings represent the

firmrsquos verifiable cash flows generated by its investments and assets that belong to its stock holders

While dividends might provide a signal for future profitability (eg Watts (1973) and Healy and

Palepu (1988) and Nissim and Ziv (2001))3 it remains the case that dividends are distributed from

accrued earnings They cannot legally exceed the book value of retained earnings

Previous research provides an additional reason for using earnings as a proxy for future cash

flows Previous literature found that prices contain information about expected earnings For

instance empirical evidence suggests that prices predict earnings better than conventional time

series models and that current price changes reflect future expected earnings shocks (see eg Beaver

Clarke and Wright (1979) Beaver Lambert and Morse (1980) Collins Kothari and Rayburn

(1987) Collins and Kothari (1989) and Kothari and Sloan (1992)) This result is also apparent in

early research such as Ball and Brown (1968) The accounting literature on prices and earnings

implies that the slope on the dividend yield with respect to earnings growth is expected to be

negative That is higher prices reflect expectations for higher future profitability Therefore

higher expected earnings push prices up and the dividend yield down

The third reason for using the aggregate earnings and earnings-dividend ratio in tests of price

volatility is the evidence concerning their predictability For instance Lamont (1998) finds that the

dividend-earnings ratio co-integrates with the dividend-price ratio and predicts returns4 Notice

that earnings growth multiplied by the dividend-earnings ratio growth is equal to dividend growth

The above implies that earnings and the earning-dividend ratio are good candidates to test for

(2004)3 In contrast DeAngelo DeAngelo and Skinner (1996) find that dividends are not a reliable signal for profitability

In addition Watts (1973) finds only weak evidence of the predictive power of dividends with respect to earnings4Vuolteenaho (2000) finds that as much as 40 of the variation in the aggregate book-to-market ratio is due to

expected profitability (Return on Equity - ROE)

4

the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and

Brown (1967)) that is priced

Based on the discussion above this paper contributes to the study of price volatility and pre-

dictability of earnings and returns by studying the information contained in the aggregate dividend

yield with regard to cash flows Specifically this paper investigates whether the dividend yield

contains information about future cash flows in terms of accounting income The results show that

expected profitability is a major source of dividend yield variation During the sample period (1952

- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield

Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield

This finding is consistent with a large body of research that studies the role of accounting income

in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball

Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings

and accruals are more strongly associated with stock prices than are dividends and cash flows

In the short-term the dividend yield is informative about earnings not dividends In the long-

term over the life of the firm earnings and dividends are the same But in the short-term such as

the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate

measure of cash flows because earnings are more timely In fact the results suggest that the

dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to

expected dividend smoothing when expected earnings are high the expected dividend-earnings

ratio is low and vice versaUsing these results this paper shows that the dividend yield would

only be able to predict dividends in the very long-term Higher expected earnings are not expected

to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope

coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-

term earnings rather than dividends is the more appropriate and more useful measure of cash

flows

As discussed above this paper finds that the dividend yield predicts both expected returns and

expected earnings growth Since the dividend yield predicts both returns and profitability it is

clear that the two are not independent In fact the results indicate a negative contemporaneous

correlation between returns and earnings growth However returns are positively correlated (021)

5See also Ribeiro (2002) and Pastor and Veronesi (2003)

5

with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower

dividend yield predicts both low expected returns and high earnings growth the contemporaneous

correlation between earnings growth and returns is expected to be negative A sharp price increase

(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence

should be positively correlated with long-term earnings growth Consequently variations in the

dividend yield due to variations in expected returns can be attributable in part to variations in

expected earnings

In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson

(2004)) find that the dividend yield has declined and lost its ability to predict returns This

paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the

permanent change the results suggest that the dividend yield is a good predictor of future excess

returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon

returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported

in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the

dividend yield

The remainder of this paper is organized as follows Section 2 provides a short description of

the data and their sources Section 3 tests whether the dividend yield contains information about

cash flows through expected accounting earnings growth Section 4 includes some additional tests

including tests aimed at determining whether the equilibrium dividend yield has declined Section

5 concludes

2 Data

The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases

for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end

requirement avoids temporal misspecifications due to different reporting and different cumulation

periods of annual earnings The returns dividends and price data are extracted from the CRSP

monthly data set The earnings item used is the earnings before extraordinary items in COMPU-

STAT The annual financial variables are measured from April of year t until March of year t+ 1

Table 1 reports summary statistics for the data used in this paper The table reports the time

series averages medians and standard deviations of the variables used in the paper The annual

6

returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is

extracted from the Fama and French three factor model data in the WRDS database

The earnings growth measure is defined as growth in the sum of annual earnings for the sample

firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)

in its measure of profitability for two reasons First accounting conservatism7 requires timely

recognition of expected declines in cash flows and at the same time does not allow firms to recognize

unverifiable expected increases in cash flows This asymmetry in recognition of economic income

results in a skewed earnings distribution (with relatively large negative values) This skewness is

likely to affect profitability measures such as average profitability growth and average return on

equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric

distribution Second earnings growth is very similar in essence to dividend growth commonly used

in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the

profitability of the market portfolio which is the variable of interest

3 The Dividend Yield and the Predictability of Earnings Divi-

dends and Returns

Previous studies suggest that the dividend yield varies mainly due to variations in expected returns

As noted above the stationarity of the dividend yield implies that it must predict either returns

or cash flows or both The evidence suggests that the dividend-price ratio contains very little

information regarding future dividend growth

Table 2 reports the estimation of the regression models

Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)

and

Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)

The table provides a short summary of previously recorded results in the literature (eg Fama and

6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)

7

French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the

long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very

similar to the results reported in Fama and French (1988) The coefficient on the dividend-price

ratio increases with horizon as well

The relation between short and long-term predictability can be interpreted by the following two

assumptions

Rt+1 = a middotDPt + ε1t+1 (3)

and

DPt+1 = ρ middotDPt + ε2t+1 (4)

Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the

coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are

all positive implying that low prices are associated with high expected returns

While the dividend-price ratio predicts returns it does not predict future dividend growth The

coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes

for different horizons Moreover the adjusted R2 for all horizons is negative

31 Predictability of Earnings

To summarize up to this point the dividend yield predicts returns but not dividend growth This

lack of dividend predictability led the finance literature to conclude that expected returns are the

main cause for aggregate price movements Although the dividend-price ratio does not predict

dividend growth it may contain information about expected cash flow through other measures

such as accounting earnings In fact as discussed above investors should be more interested in

measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends

which represent financing decisions

To test whether the dividend yield predicts earnings growth the following two regression models

were estimated for 1-10 year horizons

8

Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)

and

EtDt

Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)

Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot

[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed

as information about expected earnings growth and information about the expected earnings-

dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth

can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use

of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of

cash flows

The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains

information about cash flows in terms of earnings The dividend yield seems to be predicting long-

term earnings growth especially at the 6-year horizon and longer This result is consistent with the

conservative nature of accounting Economic gains are not recorded in a timely fashion Economic

growth at period t would result in earnings increases as much as ten years later The patterns of

predictability are similar to those of the returns predictability reported in Table 2 The coefficient

on the dividend yield increases in absolute value with the horizon as does the R2

The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend

smoothing While the dividend yield predicts future earnings growth it also predicts changes in

the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-

term and it offsets the effects of expected earnings growth The results suggest that an increase in

expected profitability is associated with an expected decline in the dividend-earnings ratio In other

words dividends do not vary as strongly as earnings and an expected earnings increase does not

8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change

qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and

Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean

surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value

or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation

9

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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Ball Ray and Philip Brown 1967 Some preliminary findings on the association between the earnings ofa firm its industry and the economy Journal of Accounting Research 5 55-77

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Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies

5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of

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of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity

Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636

Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 5: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and

Brown (1967)) that is priced

Based on the discussion above this paper contributes to the study of price volatility and pre-

dictability of earnings and returns by studying the information contained in the aggregate dividend

yield with regard to cash flows Specifically this paper investigates whether the dividend yield

contains information about future cash flows in terms of accounting income The results show that

expected profitability is a major source of dividend yield variation During the sample period (1952

- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield

Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield

This finding is consistent with a large body of research that studies the role of accounting income

in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball

Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings

and accruals are more strongly associated with stock prices than are dividends and cash flows

In the short-term the dividend yield is informative about earnings not dividends In the long-

term over the life of the firm earnings and dividends are the same But in the short-term such as

the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate

measure of cash flows because earnings are more timely In fact the results suggest that the

dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to

expected dividend smoothing when expected earnings are high the expected dividend-earnings

ratio is low and vice versaUsing these results this paper shows that the dividend yield would

only be able to predict dividends in the very long-term Higher expected earnings are not expected

to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope

coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-

term earnings rather than dividends is the more appropriate and more useful measure of cash

flows

As discussed above this paper finds that the dividend yield predicts both expected returns and

expected earnings growth Since the dividend yield predicts both returns and profitability it is

clear that the two are not independent In fact the results indicate a negative contemporaneous

correlation between returns and earnings growth However returns are positively correlated (021)

5See also Ribeiro (2002) and Pastor and Veronesi (2003)

5

with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower

dividend yield predicts both low expected returns and high earnings growth the contemporaneous

correlation between earnings growth and returns is expected to be negative A sharp price increase

(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence

should be positively correlated with long-term earnings growth Consequently variations in the

dividend yield due to variations in expected returns can be attributable in part to variations in

expected earnings

In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson

(2004)) find that the dividend yield has declined and lost its ability to predict returns This

paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the

permanent change the results suggest that the dividend yield is a good predictor of future excess

returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon

returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported

in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the

dividend yield

The remainder of this paper is organized as follows Section 2 provides a short description of

the data and their sources Section 3 tests whether the dividend yield contains information about

cash flows through expected accounting earnings growth Section 4 includes some additional tests

including tests aimed at determining whether the equilibrium dividend yield has declined Section

5 concludes

2 Data

The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases

for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end

requirement avoids temporal misspecifications due to different reporting and different cumulation

periods of annual earnings The returns dividends and price data are extracted from the CRSP

monthly data set The earnings item used is the earnings before extraordinary items in COMPU-

STAT The annual financial variables are measured from April of year t until March of year t+ 1

Table 1 reports summary statistics for the data used in this paper The table reports the time

series averages medians and standard deviations of the variables used in the paper The annual

6

returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is

extracted from the Fama and French three factor model data in the WRDS database

The earnings growth measure is defined as growth in the sum of annual earnings for the sample

firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)

in its measure of profitability for two reasons First accounting conservatism7 requires timely

recognition of expected declines in cash flows and at the same time does not allow firms to recognize

unverifiable expected increases in cash flows This asymmetry in recognition of economic income

results in a skewed earnings distribution (with relatively large negative values) This skewness is

likely to affect profitability measures such as average profitability growth and average return on

equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric

distribution Second earnings growth is very similar in essence to dividend growth commonly used

in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the

profitability of the market portfolio which is the variable of interest

3 The Dividend Yield and the Predictability of Earnings Divi-

dends and Returns

Previous studies suggest that the dividend yield varies mainly due to variations in expected returns

As noted above the stationarity of the dividend yield implies that it must predict either returns

or cash flows or both The evidence suggests that the dividend-price ratio contains very little

information regarding future dividend growth

Table 2 reports the estimation of the regression models

Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)

and

Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)

The table provides a short summary of previously recorded results in the literature (eg Fama and

6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)

7

French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the

long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very

similar to the results reported in Fama and French (1988) The coefficient on the dividend-price

ratio increases with horizon as well

The relation between short and long-term predictability can be interpreted by the following two

assumptions

Rt+1 = a middotDPt + ε1t+1 (3)

and

DPt+1 = ρ middotDPt + ε2t+1 (4)

Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the

coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are

all positive implying that low prices are associated with high expected returns

While the dividend-price ratio predicts returns it does not predict future dividend growth The

coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes

for different horizons Moreover the adjusted R2 for all horizons is negative

31 Predictability of Earnings

To summarize up to this point the dividend yield predicts returns but not dividend growth This

lack of dividend predictability led the finance literature to conclude that expected returns are the

main cause for aggregate price movements Although the dividend-price ratio does not predict

dividend growth it may contain information about expected cash flow through other measures

such as accounting earnings In fact as discussed above investors should be more interested in

measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends

which represent financing decisions

To test whether the dividend yield predicts earnings growth the following two regression models

were estimated for 1-10 year horizons

8

Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)

and

EtDt

Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)

Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot

[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed

as information about expected earnings growth and information about the expected earnings-

dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth

can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use

of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of

cash flows

The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains

information about cash flows in terms of earnings The dividend yield seems to be predicting long-

term earnings growth especially at the 6-year horizon and longer This result is consistent with the

conservative nature of accounting Economic gains are not recorded in a timely fashion Economic

growth at period t would result in earnings increases as much as ten years later The patterns of

predictability are similar to those of the returns predictability reported in Table 2 The coefficient

on the dividend yield increases in absolute value with the horizon as does the R2

The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend

smoothing While the dividend yield predicts future earnings growth it also predicts changes in

the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-

term and it offsets the effects of expected earnings growth The results suggest that an increase in

expected profitability is associated with an expected decline in the dividend-earnings ratio In other

words dividends do not vary as strongly as earnings and an expected earnings increase does not

8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change

qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and

Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean

surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value

or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation

9

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 6: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower

dividend yield predicts both low expected returns and high earnings growth the contemporaneous

correlation between earnings growth and returns is expected to be negative A sharp price increase

(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence

should be positively correlated with long-term earnings growth Consequently variations in the

dividend yield due to variations in expected returns can be attributable in part to variations in

expected earnings

In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson

(2004)) find that the dividend yield has declined and lost its ability to predict returns This

paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the

permanent change the results suggest that the dividend yield is a good predictor of future excess

returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon

returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported

in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the

dividend yield

The remainder of this paper is organized as follows Section 2 provides a short description of

the data and their sources Section 3 tests whether the dividend yield contains information about

cash flows through expected accounting earnings growth Section 4 includes some additional tests

including tests aimed at determining whether the equilibrium dividend yield has declined Section

5 concludes

2 Data

The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases

for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end

requirement avoids temporal misspecifications due to different reporting and different cumulation

periods of annual earnings The returns dividends and price data are extracted from the CRSP

monthly data set The earnings item used is the earnings before extraordinary items in COMPU-

STAT The annual financial variables are measured from April of year t until March of year t+ 1

Table 1 reports summary statistics for the data used in this paper The table reports the time

series averages medians and standard deviations of the variables used in the paper The annual

6

returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is

extracted from the Fama and French three factor model data in the WRDS database

The earnings growth measure is defined as growth in the sum of annual earnings for the sample

firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)

in its measure of profitability for two reasons First accounting conservatism7 requires timely

recognition of expected declines in cash flows and at the same time does not allow firms to recognize

unverifiable expected increases in cash flows This asymmetry in recognition of economic income

results in a skewed earnings distribution (with relatively large negative values) This skewness is

likely to affect profitability measures such as average profitability growth and average return on

equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric

distribution Second earnings growth is very similar in essence to dividend growth commonly used

in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the

profitability of the market portfolio which is the variable of interest

3 The Dividend Yield and the Predictability of Earnings Divi-

dends and Returns

Previous studies suggest that the dividend yield varies mainly due to variations in expected returns

As noted above the stationarity of the dividend yield implies that it must predict either returns

or cash flows or both The evidence suggests that the dividend-price ratio contains very little

information regarding future dividend growth

Table 2 reports the estimation of the regression models

Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)

and

Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)

The table provides a short summary of previously recorded results in the literature (eg Fama and

6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)

7

French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the

long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very

similar to the results reported in Fama and French (1988) The coefficient on the dividend-price

ratio increases with horizon as well

The relation between short and long-term predictability can be interpreted by the following two

assumptions

Rt+1 = a middotDPt + ε1t+1 (3)

and

DPt+1 = ρ middotDPt + ε2t+1 (4)

Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the

coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are

all positive implying that low prices are associated with high expected returns

While the dividend-price ratio predicts returns it does not predict future dividend growth The

coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes

for different horizons Moreover the adjusted R2 for all horizons is negative

31 Predictability of Earnings

To summarize up to this point the dividend yield predicts returns but not dividend growth This

lack of dividend predictability led the finance literature to conclude that expected returns are the

main cause for aggregate price movements Although the dividend-price ratio does not predict

dividend growth it may contain information about expected cash flow through other measures

such as accounting earnings In fact as discussed above investors should be more interested in

measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends

which represent financing decisions

To test whether the dividend yield predicts earnings growth the following two regression models

were estimated for 1-10 year horizons

8

Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)

and

EtDt

Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)

Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot

[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed

as information about expected earnings growth and information about the expected earnings-

dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth

can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use

of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of

cash flows

The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains

information about cash flows in terms of earnings The dividend yield seems to be predicting long-

term earnings growth especially at the 6-year horizon and longer This result is consistent with the

conservative nature of accounting Economic gains are not recorded in a timely fashion Economic

growth at period t would result in earnings increases as much as ten years later The patterns of

predictability are similar to those of the returns predictability reported in Table 2 The coefficient

on the dividend yield increases in absolute value with the horizon as does the R2

The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend

smoothing While the dividend yield predicts future earnings growth it also predicts changes in

the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-

term and it offsets the effects of expected earnings growth The results suggest that an increase in

expected profitability is associated with an expected decline in the dividend-earnings ratio In other

words dividends do not vary as strongly as earnings and an expected earnings increase does not

8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change

qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and

Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean

surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value

or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation

9

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is

extracted from the Fama and French three factor model data in the WRDS database

The earnings growth measure is defined as growth in the sum of annual earnings for the sample

firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)

in its measure of profitability for two reasons First accounting conservatism7 requires timely

recognition of expected declines in cash flows and at the same time does not allow firms to recognize

unverifiable expected increases in cash flows This asymmetry in recognition of economic income

results in a skewed earnings distribution (with relatively large negative values) This skewness is

likely to affect profitability measures such as average profitability growth and average return on

equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric

distribution Second earnings growth is very similar in essence to dividend growth commonly used

in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the

profitability of the market portfolio which is the variable of interest

3 The Dividend Yield and the Predictability of Earnings Divi-

dends and Returns

Previous studies suggest that the dividend yield varies mainly due to variations in expected returns

As noted above the stationarity of the dividend yield implies that it must predict either returns

or cash flows or both The evidence suggests that the dividend-price ratio contains very little

information regarding future dividend growth

Table 2 reports the estimation of the regression models

Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)

and

Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)

The table provides a short summary of previously recorded results in the literature (eg Fama and

6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)

7

French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the

long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very

similar to the results reported in Fama and French (1988) The coefficient on the dividend-price

ratio increases with horizon as well

The relation between short and long-term predictability can be interpreted by the following two

assumptions

Rt+1 = a middotDPt + ε1t+1 (3)

and

DPt+1 = ρ middotDPt + ε2t+1 (4)

Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the

coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are

all positive implying that low prices are associated with high expected returns

While the dividend-price ratio predicts returns it does not predict future dividend growth The

coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes

for different horizons Moreover the adjusted R2 for all horizons is negative

31 Predictability of Earnings

To summarize up to this point the dividend yield predicts returns but not dividend growth This

lack of dividend predictability led the finance literature to conclude that expected returns are the

main cause for aggregate price movements Although the dividend-price ratio does not predict

dividend growth it may contain information about expected cash flow through other measures

such as accounting earnings In fact as discussed above investors should be more interested in

measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends

which represent financing decisions

To test whether the dividend yield predicts earnings growth the following two regression models

were estimated for 1-10 year horizons

8

Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)

and

EtDt

Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)

Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot

[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed

as information about expected earnings growth and information about the expected earnings-

dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth

can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use

of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of

cash flows

The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains

information about cash flows in terms of earnings The dividend yield seems to be predicting long-

term earnings growth especially at the 6-year horizon and longer This result is consistent with the

conservative nature of accounting Economic gains are not recorded in a timely fashion Economic

growth at period t would result in earnings increases as much as ten years later The patterns of

predictability are similar to those of the returns predictability reported in Table 2 The coefficient

on the dividend yield increases in absolute value with the horizon as does the R2

The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend

smoothing While the dividend yield predicts future earnings growth it also predicts changes in

the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-

term and it offsets the effects of expected earnings growth The results suggest that an increase in

expected profitability is associated with an expected decline in the dividend-earnings ratio In other

words dividends do not vary as strongly as earnings and an expected earnings increase does not

8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change

qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and

Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean

surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value

or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation

9

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

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21

Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

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Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

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Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 8: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the

long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very

similar to the results reported in Fama and French (1988) The coefficient on the dividend-price

ratio increases with horizon as well

The relation between short and long-term predictability can be interpreted by the following two

assumptions

Rt+1 = a middotDPt + ε1t+1 (3)

and

DPt+1 = ρ middotDPt + ε2t+1 (4)

Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the

coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are

all positive implying that low prices are associated with high expected returns

While the dividend-price ratio predicts returns it does not predict future dividend growth The

coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes

for different horizons Moreover the adjusted R2 for all horizons is negative

31 Predictability of Earnings

To summarize up to this point the dividend yield predicts returns but not dividend growth This

lack of dividend predictability led the finance literature to conclude that expected returns are the

main cause for aggregate price movements Although the dividend-price ratio does not predict

dividend growth it may contain information about expected cash flow through other measures

such as accounting earnings In fact as discussed above investors should be more interested in

measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends

which represent financing decisions

To test whether the dividend yield predicts earnings growth the following two regression models

were estimated for 1-10 year horizons

8

Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)

and

EtDt

Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)

Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot

[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed

as information about expected earnings growth and information about the expected earnings-

dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth

can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use

of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of

cash flows

The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains

information about cash flows in terms of earnings The dividend yield seems to be predicting long-

term earnings growth especially at the 6-year horizon and longer This result is consistent with the

conservative nature of accounting Economic gains are not recorded in a timely fashion Economic

growth at period t would result in earnings increases as much as ten years later The patterns of

predictability are similar to those of the returns predictability reported in Table 2 The coefficient

on the dividend yield increases in absolute value with the horizon as does the R2

The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend

smoothing While the dividend yield predicts future earnings growth it also predicts changes in

the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-

term and it offsets the effects of expected earnings growth The results suggest that an increase in

expected profitability is associated with an expected decline in the dividend-earnings ratio In other

words dividends do not vary as strongly as earnings and an expected earnings increase does not

8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change

qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and

Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean

surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value

or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation

9

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)

and

EtDt

Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)

Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot

[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed

as information about expected earnings growth and information about the expected earnings-

dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth

can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use

of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of

cash flows

The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains

information about cash flows in terms of earnings The dividend yield seems to be predicting long-

term earnings growth especially at the 6-year horizon and longer This result is consistent with the

conservative nature of accounting Economic gains are not recorded in a timely fashion Economic

growth at period t would result in earnings increases as much as ten years later The patterns of

predictability are similar to those of the returns predictability reported in Table 2 The coefficient

on the dividend yield increases in absolute value with the horizon as does the R2

The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend

smoothing While the dividend yield predicts future earnings growth it also predicts changes in

the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-

term and it offsets the effects of expected earnings growth The results suggest that an increase in

expected profitability is associated with an expected decline in the dividend-earnings ratio In other

words dividends do not vary as strongly as earnings and an expected earnings increase does not

8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change

qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and

Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean

surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value

or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation

9

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

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Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

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Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

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Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 10: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =

Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend

growth Hence the market anticipates dividend smoothing

32 Understanding the Lack of Dividend Predictability

The results in Figure 1 summarize and illustrate the relation between earnings growth expected

dividend-earnings ratio and the expectations for future dividend growth The figure plots the

expected earnings growth and expected dividend-earnings ratio from estimating

ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)

and

ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)

The implied expected log dividend growth is the sum of the predicted values from the above

regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of

expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate

Notice that while there is an increase in expected earnings growth the expected dividend-

earnings ratio declines The resulting implied dividend growth is very weak There are two different

interpretations for this result First it is possible that the dividend yield predicts dividend growth

in the very long-horizon Second it is possible that the dividend smoothness is endogenous

- implying that dividend growth might be unpredictable10 Since some recent studies find some

evidence of dividend predictability the first interpretation ie dividend yield predicts dividends

only in the very long horizon is more likely The results show that firms are expected to keep

reserves when earnings are high and use them when earnings are low resulting in smooth dividends

To understand the lack of dividend predictability consider the following equations

∆10et+10 = a middot dpt + t+10 (9)

∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)

10Apart from exogenous shocks such as recessions (see Section 41)

10

dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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22

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23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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dpt+1 = ρ middot dpt + ψt+1 (11)

where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =

ln (DPt)

Since Figure 1 shows that the implied dividend growth appears only over the long term the

analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies

that

dpt+10 = ρ10 middot dpt + error (12)

and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that

∆10dt+10 = (a+ b) middot dpt + error (13)

Using Equations (12) and (13) the implied long-term dividend growth is given by

∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)

imiddot dpt + error (14)

for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and

ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The

following table reports the implied dividend growth given these results

i Implied Dividend Growth Coefficient

1 -008

2 -013

3 -017

4 -019

The table above represents the lack of dividend predictability Since earnings growth is only

predictable in the long-term about five years ahead horizon and longer dividends are unpredictable

in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth

coefficient is only -019 The table implies that to find dividend predictability using the dividend

yield one must use very long-term tests Such a test is not feasible with the available data and

11

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

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Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

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nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 12: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

long horizon tests might be unreliable In sum earnings are more timely than dividends and they

provide a better measure for cash flows than dividends

33 A Variance Decomposition Approach

The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who

decompose the variance of the dividend-price ratio to two major components expected returns and

expected dividend growth12 This approach contributes by estimating how variation in expected

profitability affects the dividend yield (economic significance) In other words the method tests

how much of the variation in the dividend-price ratio is attributable to information about expected

profitability For brevity this paper provides only the key steps Note

Rt+1 = (Pt+1 +Dt+1) Pt (15)

Equation (15) can be rewritten so that the price-dividend ratio can be written as

PtDt

= Rminus1t+1

micro1 +

Pt+1Dt+1

paraDt+1

Dt(16)

Taking natural logs yields

pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1

acute(17)

The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of

the last term yields

pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)

where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is

approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the

following expression

dt minus pt = const+EinfinXj=1

ρjminus1 (rt+j minus∆dt+j) (19)

11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)

12

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 13: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

Equation (18) implies that the variance of the dividend yield can be decomposed into two parts

predictability of returns and dividend predictability

var (dt minus pt) = cov

⎛⎝dt minus ptinfinXj=1

ρjminus1rt+j

⎞⎠minus cov

⎛⎝dt minus ptinfinXj=1

ρjminus1∆dt+j

⎞⎠ (20)

Table 4 reports the results for the estimation of Equation (20) Most of the variation in the

dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand

dividend growth variation does not generate variation in the dividend-price ratio These results are

consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the

results in Table 2 When cash flow information is restricted to dividend growth this result suggests

that the dividend yield does not contain much information about cash flows

Equation (19) can be modified slightly to include other sources of information about cash flow

Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source

of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can

be written as

dt minus pt = const+Et

infinXj=1

ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)

The corresponding variance decomposition can be decomposed into three factors returns pre-

dictability earnings predictability and earnings-dividend ratio predictability The sum of the last

two parts is the dividend growth The variance decomposition is then decomposed further into the

same three factors and with additional decomposition for different horizons one through five and

six through ten periods ahead14

The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and

longer) earnings growth seems more predictable than the shorter horizon

13

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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21

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22

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23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 14: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

var (dt minus pt) = cov

⎛⎝dt minus pt5X

j=1

ρjminus1rt+j

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1rt+j

⎞⎠ (22)

minuscov

⎛⎝dt minus pt5X

j=1

ρjminus1∆et+j

⎞⎠minus cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆et+j

⎞⎠+cov

⎛⎝dt minus pt5X

j=1

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ cov

⎛⎝dt minus pt10Xj=6

ρjminus1∆ (et+j minus dt+j)

⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)

Table 4 reports the results from estimating Equation (22) The results are consistent with the

results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-

dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation

In the infinite horizon equation Equation (19) we can replace dividends with earnings because

they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in

long horizon tests it does not matter whether we use dividends or earnings However the results

in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows

and changes in expected profitability are priced On the other hand short-term dividend variation

is not reflected in prices

34 The Determinants of the Dividend Yield

The analysis below provides additional inferences on whether dividends or earnings determine

the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10

j=1 ρjminus1rt+j Elowastt equivP10

j=1 ρjminus1∆et+j EDlowastt equiv

P10j=1 ρ

jminus1∆(e minus d)t+j and Dlowastt equivP10

j=1 ρjminus1∆dt+j Table 5 reports the

correlations between these variables The dividend yield is highly correlated with both expected

profitability growth (-07) and expected returns (085) On the other hand expected dividend

growth does seem to be correlated with the dividend yield

The apparent strong correlation between earnings growth and returns is not surprising First

investorsrsquo preferences of holding risk varies with business conditions Second expected profitability

is expected to vary with business conditions For example expected returns are high in recessions

On the other hand expected profitability is low in recessions Note that this result does not contra-

dict previous findings that unexpected earnings are positively associated with positive unexpected

14

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on

equity capital The Accounting Review 79 (1) 73-95

21

Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity

Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636

Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 15: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

returns (eg Ball and Brown (1968))

An additional method of testing different determinants of the dividend yield is a simple regres-

sion analysis15 In particular Table 6 uses the following regression model

dt minus pt = δ0 + δ1Rlowastt + δ2E

lowastt + δ3D

lowastt + δ4ρ

10(dminus p)t+11 + ζt (23)

The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by

expected earnings growth and not dividend growth The coefficient on expected profitability growth

is negative and statistically significant for all model specifications The coefficient on dividend

growth is not statistically significant in any of the specifications Moreover the adjusted R2 for

the regression including earnings alone is 05 compared to -002 for dividends In sum the results

in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns

determine the equilibrium aggregate dividend-price ratio

The results in Tables 2 3 and 5 point to the strong relation between expected returns and

expected earnings Since the same variable (the dividend yield) predicts both earnings and returns

(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)

Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is

highly correlated with Elowastt ) These results suggest that variations in expected returns are due in

part to variations in expected earnings growth

Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed

into two orthogonal factors of expected returns and expected cash flows for both earnings and

dividends Since expected returns include both a cash flow component and an expected returns

component the expected returns determinant was decomposed into returns orthogonal to cash

flows as follows

Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)

was estimated for dividends and

Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)

15Kothari and Shanken (1992) use a similar regression analysis using dividends

15

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity

Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

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Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

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Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 16: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

for earnings

Consider the following linear model of the dividend yield

dt minus pt = bX0 + bX1 Xlowastt + bX2 υ

Xt + ζXt (26)

for X = E and D The variance of the dividend yield can then be decomposed into

V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast

t ) +iexclbX2cent2V ar

iexclυXtcent+ V ar

iexclζXtcent

(27)

Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-

esis that the equilibrium dividend yield is determined in part by cash flow information as reflected

by earnings However the dividend yield does not seem to be affected by expectations of future

dividend growth Moreover the results indicate that expected returns themselves contain informa-

tion about future cash flows The adjusted R2 is similar when using dividends and earnings That

is the expectations of returns contain information about expectations of cash flows16 as reflected

by earnings For instance Table 5 shows a very high correlation between long term returns and

long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50

of the variation in the dividend yield compared to only 1 that dividends explain

4 Additional Considerations

This section provides some additional tests and results related to the dividend yield The evidence

explored in this section is consistent with a permanent decline in the dividend yield during the

1990s Controlling for this shift restores the predictive power of the dividend yield with respect

to expected returns This section also explores some additional related issues such as raw returns

versus excess returns and the information content of dividend growth with respect to earnings and

returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)

16

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

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21

Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

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Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

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Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 17: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

41 The Dividend Yield in the 1990s

Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive

power with respect to returns in the 1990s and is lower than its past mean This finding suggests

that one of the following is true First it is possible that the dividend yield is not as informative

about expected returns as suggested by prior research Second it is possible that the dividend

yield will increase to its past mean due to either higher dividends andor lower returns Finally

it is possible that the dividend yield has declined to a new lower equilibrium stationary level The

following test supports the latter interpretation of the results Controlling for a permanent shift

in the dividend yield it seems that the dividend yield is highly informative about expected excess

returns (including the 1990s) and it did not lose its predictive power

To control for a permanent shift in the dividend yield the following regression model was used

DPt = δ0 + δ1 middotDUM90s+ τ t (28)

where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or

equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted

in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has

maintained its ability to predict excess returns and earnings growth Table 8 reports results for the

following regression models

Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)

and

Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)

The results are consistent with a permanent shift in the dividend yield The results suggest that

the dividend yield did not loose its ability to predict excess returns and earnings growth in the

1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for

the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018

18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and

earnings the dividend yields during the 1990s are mostly excluded

17

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

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of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

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21

Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity

Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

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Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 18: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

411 Why Has the Dividend Yield Declined

The dividend yield seems to have declined during the 1990s This result is consistent with Fama and

French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the

decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low

earnings and high growth opportunities has increased significantly in the 1990s Moreover they find

that firms are less likely to pay dividends even when controlling for the change in characteristics

In the 1990s many firms engaged in RampD activities and stock markets were used more extensively

in financing such projects These projects are high growth projects with low short-term cash flows

resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price

ratio

42 An Impulse Response Function

Another method of illustrating the point presented in Figure 1 is using an impulse response function

In particular using the following set of equations to illustrate the effects of a shock to the dividend

yield until it converges back to its equilibrium level

DPt+1 = ρ middotDPt + ε1t+1 (31)

Rt+1 = a middotDPt + ε2t+1 (32)

Et+iEt = b middotDPt + ε3t+1 (33)

and

EtDt

Et+iDt+i= c middotDPt + ε4t+1 (34)

Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at

the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is

necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot

DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c

18

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

References

Ball Ray 2001 Infrastructure Requirements for an economically efficient system of public financialreporting and disclosure Brookings - Wharton Papers on Financial Services

Ball Ray and Philip Brown 1967 Some preliminary findings on the association between the earnings ofa firm its industry and the economy Journal of Accounting Research 5 55-77

Ball Ray and Philip Brown 1968 An empirical evaluation of accounting income numbers Journal ofAccounting Research 6 159-178

Ball Ray SP Kothari and Ashok Robin 2000 The effect of international institutional factors onproperties of accounting earnings Journal of Accounting and Economics 29 1-51

Basu S 1997 The conservatism principle and the asymmetric timeliness of earnings Journal of Ac-counting and Economics 24 3-37

Beaver William H Roger Clarke William F Wright 1979 The information content of security pricesJournal of Accounting and Economics 17 316-340

Beaver William H Richard Lambert and Dale Morse 1980The information content of security pricesJournal of Accounting and Economics 2 3-28

Callen Jeffrey L and Dan Segal 2004 Do accruals drive stock returns a variance decompositionanalysis Journal of Accounting Research 42 527-560

Campbell John Y 1991 A variance decomposition for stock returns Economic Journal 101 157-179Campbell John Y and John Ammer 1993 What moves the stock and bond markets A variance

decomposition for long-term asset returns Journal of Finance 48 3-37Campbell John Y and Robert J Shiller 1988a The dividend-price ratio and expectations of future

dividends and discount factors Review of Financial Studies 1 195-227Campbell John Y and Robert J Shiller 1988b Stock prices earnings and expected dividends The

Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies

5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of

Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of

earnings response coefficients Journal of Accounting and Economics 11 143-181Collins Daniel W SP Kothari and Judy D Rayburn 1987 Firm size and the information content of

prices with respect to earnings Journal of Accounting and Economics 9 111-138DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1992 Dividends and losses Journal of

Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling

and the disappearance of sustained earnings growth Journal of Financial Economics 40 341-371Dechow Patricia 1994 Accounting earnings and cash flows as measures of firm performance Journal

of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on

equity capital The Accounting Review 79 (1) 73-95

21

Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity

Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636

Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 19: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

The impulse response function is plotted in Figure 2 The pattern in this figure is consistent

with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings

and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the

expected effect on the dividendsearnings ratio implying long-term dividend decline

43 The Information Content of Dividend Growth

Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends

can provide information about future profitability To test the implications of the predictive power

of dividend increases for future profitability the following model was estimated

Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)

The model was estimated including and excluding the dividend yield The results (not reported) are

not consistent with dividend growth predicting future profitability growth δ2 is generally negative

and is mostly not statistically significant In other words on the aggregate level dividend growth

does not seem to signal profitability growth This result suggests that the information content of

the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)

44 Raw Returns versus Excess Returns

The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)

These tests were replicated using raw returns The results do not vary qualitatively The paper

chose excess returns to show that there are time-varying risk premiums However the variance

decomposition approach requires the use of raw returns When Table 4 is estimated using excess

returns the sum of the decomposition-components does not add up to 100 Therefore Table 4

utilizes the raw returns For the same reason Tables 5-7 use raw returns as well

5 Conclusion

The paper investigates the implications of accounting profitability for the information content of the

dividend-price ratio Previous studies suggest that the dividend yield does not contain information

about cash flows ie the dividend yield does not predict dividend growth However the results

19

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

References

Ball Ray 2001 Infrastructure Requirements for an economically efficient system of public financialreporting and disclosure Brookings - Wharton Papers on Financial Services

Ball Ray and Philip Brown 1967 Some preliminary findings on the association between the earnings ofa firm its industry and the economy Journal of Accounting Research 5 55-77

Ball Ray and Philip Brown 1968 An empirical evaluation of accounting income numbers Journal ofAccounting Research 6 159-178

Ball Ray SP Kothari and Ashok Robin 2000 The effect of international institutional factors onproperties of accounting earnings Journal of Accounting and Economics 29 1-51

Basu S 1997 The conservatism principle and the asymmetric timeliness of earnings Journal of Ac-counting and Economics 24 3-37

Beaver William H Roger Clarke William F Wright 1979 The information content of security pricesJournal of Accounting and Economics 17 316-340

Beaver William H Richard Lambert and Dale Morse 1980The information content of security pricesJournal of Accounting and Economics 2 3-28

Callen Jeffrey L and Dan Segal 2004 Do accruals drive stock returns a variance decompositionanalysis Journal of Accounting Research 42 527-560

Campbell John Y 1991 A variance decomposition for stock returns Economic Journal 101 157-179Campbell John Y and John Ammer 1993 What moves the stock and bond markets A variance

decomposition for long-term asset returns Journal of Finance 48 3-37Campbell John Y and Robert J Shiller 1988a The dividend-price ratio and expectations of future

dividends and discount factors Review of Financial Studies 1 195-227Campbell John Y and Robert J Shiller 1988b Stock prices earnings and expected dividends The

Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies

5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of

Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of

earnings response coefficients Journal of Accounting and Economics 11 143-181Collins Daniel W SP Kothari and Judy D Rayburn 1987 Firm size and the information content of

prices with respect to earnings Journal of Accounting and Economics 9 111-138DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1992 Dividends and losses Journal of

Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling

and the disappearance of sustained earnings growth Journal of Financial Economics 40 341-371Dechow Patricia 1994 Accounting earnings and cash flows as measures of firm performance Journal

of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on

equity capital The Accounting Review 79 (1) 73-95

21

Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity

Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636

Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 20: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

presented in this paper are consistent with predictability of accounting profitability These results

suggest that the cash flow information embedded in the dividend-price ratio shows up in terms

of profitability growth (free cash flow) and not dividend growth Although it is unlikely that

dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the

aggregate level investors are more interested in measures of free cash flow than dividends The

dividend growth is much smoother less predictable and much less timely than earnings Thus

especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the

literature) earnings rather than dividends are more appropriate and are likely to provide more

insight on the information embedded in prices

As an approximation over the life of the firm earnings and dividends are the same However

it is unclear how long it takes for a profitability shock to translate into dividends Long-term

dividend growth is affected by many different profitability shocks and might be difficult to predict

For example a $100 profitability shock in any year might translate into a $4 dividend shock for

25 years which would be difficult to detect in the data particularly given other past and future

profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend

growth as reflected in the dividend yield is relatively weak

This paper also shows that expected returns contain a significant cash flow component Since

the dividend yield predicts both profitability and returns the two cannot be independent This

means that variation in the dividend yield due to expectations of returns also reflects variation in

expected profitability

20

References

Ball Ray 2001 Infrastructure Requirements for an economically efficient system of public financialreporting and disclosure Brookings - Wharton Papers on Financial Services

Ball Ray and Philip Brown 1967 Some preliminary findings on the association between the earnings ofa firm its industry and the economy Journal of Accounting Research 5 55-77

Ball Ray and Philip Brown 1968 An empirical evaluation of accounting income numbers Journal ofAccounting Research 6 159-178

Ball Ray SP Kothari and Ashok Robin 2000 The effect of international institutional factors onproperties of accounting earnings Journal of Accounting and Economics 29 1-51

Basu S 1997 The conservatism principle and the asymmetric timeliness of earnings Journal of Ac-counting and Economics 24 3-37

Beaver William H Roger Clarke William F Wright 1979 The information content of security pricesJournal of Accounting and Economics 17 316-340

Beaver William H Richard Lambert and Dale Morse 1980The information content of security pricesJournal of Accounting and Economics 2 3-28

Callen Jeffrey L and Dan Segal 2004 Do accruals drive stock returns a variance decompositionanalysis Journal of Accounting Research 42 527-560

Campbell John Y 1991 A variance decomposition for stock returns Economic Journal 101 157-179Campbell John Y and John Ammer 1993 What moves the stock and bond markets A variance

decomposition for long-term asset returns Journal of Finance 48 3-37Campbell John Y and Robert J Shiller 1988a The dividend-price ratio and expectations of future

dividends and discount factors Review of Financial Studies 1 195-227Campbell John Y and Robert J Shiller 1988b Stock prices earnings and expected dividends The

Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies

5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of

Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of

earnings response coefficients Journal of Accounting and Economics 11 143-181Collins Daniel W SP Kothari and Judy D Rayburn 1987 Firm size and the information content of

prices with respect to earnings Journal of Accounting and Economics 9 111-138DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1992 Dividends and losses Journal of

Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling

and the disappearance of sustained earnings growth Journal of Financial Economics 40 341-371Dechow Patricia 1994 Accounting earnings and cash flows as measures of firm performance Journal

of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows

Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on

equity capital The Accounting Review 79 (1) 73-95

21

Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity

Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636

Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 21: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

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Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636

Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

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Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

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nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

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Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143

Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity

Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25

Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49

Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56

Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43

Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636

Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731

Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34

Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175

Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109

Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210

Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203

Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171

Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test

when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-

nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and

empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political

Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of

Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance

56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary

Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of

Finance 58 1749-1790

22

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 23: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation

of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working

Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to

current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211

23

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Page 24: Resolving the Price Volatility Puzzle: The Role of Earningsw4.stern.nyu.edu/accounting/docs/speaker_papers/spring2005/Sadka... · Resolving the Price Volatility Puzzle: The Role of

-2

-15

-1

-05

0

05

1

15

2

25

1 2 3 4 5 6 7 8 9 10

Dividends-Earnings Ratio Earnings Dividends

Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon

DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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DP Returns Earnigns Growth Growth in EarningsDividends

Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield

DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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DPtMean 0039

Median 0037Standard Deviation 0012

Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897

Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838

Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722

Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349

Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472

Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662

(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736

Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252

Value-Weighted Market Index

Table 1Summary Statistics

The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December

Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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Intercept DPt R2

Rtrarrt+1 -0064 3600 0058-084 191 -

Rtrarrt+2 -0047 5198 0056-032 148 -

Rtrarrt+3 -0107 6378 0076-075 167 -

Rtrarrt+4 -0176 12892 0122-046 149 -

Rtrarrt+5 -0360 19484 0191-071 172 -

Rtrarrt+10 -1691 61140 0552-284 413 -

Dt+1Dt 1136 -1888 -00011298 -088 -

Dt+2Dt 1166 -1072 -00151939 -071 -

Dt+3Dt 1174 0217 -00211314 010 -

Dt+4Dt 1228 0450 -00211228 019 -

Dt+5Dt 1255 1473 -00171211 065 -

Dt+10Dt 1828 -2521 -0019903 -071 -

Table 2Predicting Returns and Dividends with the Dividend-Price Ratio

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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Intercept DPt R2

Et+1Et 1193 -2344 00262277 -188 -

Et+2Et 1223 -0549 -0020724 -015 -

Et+3Et 1293 0498 -0021468 008 -

Et+4Et 1532 -2194 -0017424 -028 -

Et+5Et 1807 -5495 -0002439 -062 -

Et+6Et 2195 -11226 0037555 -134 -

Et+7Et 2689 -19099 0112706 -233 -

Et+8Et 3265 -28619 0215747 -293 -

Et+9Et 3640 -32743 0250684 -263 -

Et+10Et 4028 -37169 0317667 -265 -

(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -

(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -

(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -

(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -

(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -

(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -

(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -

(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -

(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -

(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -

Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio

The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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Var(d t -p t ) 0053 0053 005310000 10000 10000

Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)

Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)

Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)

Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)

Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)

Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)

Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)

Table 4Variance Decomposition for the Dividend-Price Ratio

The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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d t -p t R t E

t ED t D

t ρ -11 (d-p) t+11

d t -p t 1

R t 08532 1

(0000)

E t -07055 -06922 1

(0000) (0000)

ED t -05493 -04849 07724 1

(00002) (00013) (0000)

D t -00881 -01707 01346 -05255 1

(0584) (02858) (04016) (00004)

ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)

Table 5Correlation Matrix

The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-

d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December

Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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Dependant Variable Intercept R t E

t ED t D

t ρ -11 (d-p) t+11 adj-R2

d t -p t -313 -018 -002(3481) (-084)

d t -p t -266 -070 050(-2974) (-677)

d t -p t -266 -071 001 047(-2426) (-690) (012)

d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)

d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)

Table 6Regression Analysis

The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-

1∆et+j Rt=sum1

10ρj-1rt+j Dt=sum1

10ρj-1∆dt+j EDt=sum1

10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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Dependant Variable Intercept E t (b E

1 ) D t (b D

1 ) υ Et (b E

2 ) υ Dt (b D

2 ) adj-R2

d t -p t -314 -012 060 072(-2917) (-057) (696)

d t -p t -266 -070 048 074(-4222) (-999) (353)

Dependant Variable Total (b E1 ) 2 Var(E

t ) (b D1 ) 2 Var(D

t ) (b E2 ) 2 Var(υ E

t ) (b D2 ) 2 Var(υ D

t ) ErrorVar(d t -p t ) 0054 0000 0039 0015

(100) (1) (72) (27)

Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)

Table 7Analysis of the Dividend Yield Variance

Panel A OLS results

Panel B Analysis of Variance

The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E

t=sum110ρj-1∆et+j R

t=sum110ρj-1rt+j D

t=sum110ρj-1∆dt+j ED

t=sum110ρj-1∆(e-d)t+j υX

t is estimated for X=E and X=D as follows R

t=φ0+ φ1Xt+ υX

t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses

Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2

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Intercept τ t R2

Rtrarrt+1 0079 5188 0096381 285 -

Rtrarrt+2 0160 8705 0142466 249 -

Rtrarrt+3 0145 6469 0059377 146 -

Rtrarrt+4 0332 21780 0330473 387 -

Rtrarrt+5 0413 30316 0445476 423 -

Rtrarrt+10 0860 62809 0619520 507 -

Et+1Et 1103 -3318 00415929 -216 -

Et+2Et 1220 -3694 00073213 -131 -

Et+3Et 1348 -3651 -00062391 -114 -

Et+4Et 1462 -2717 -00171884 -056 -

Et+5Et 1588 -2902 -00171632 -043 -

Et+6Et 1746 -8558 00071674 -114 -

Et+7Et 1921 -16304 00661797 -197 -

Et+8Et 2107 -27129 01801983 -278 -

Et+9Et 2307 -33264 02532118 -286 -

Et+10Et 2505 -40690 03922239 -335 -

Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s

The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002

The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2