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J O U R N A L O F F I N A N C I A L A N D Q U A N T I T A TI V E A N A L Y S I S V O L . 4 1 , N O . 2 , J U N E 2 0 0 6COPYRIGHT 2006, SCHOOL OF BUSINESS ADMINISTRATION. UNIVERSITY OF WASHINGTON, SEATTLE, WA 98195

Dividend Smoothing and Debt RatingsVarouj A. Aivazian, Laurence Booth, and Sean Cleary*

AbstractWe find that firms that regularly access public debt (bond) markets are more likely topay a dividend and subsequently follow a dividend smoothing policy than firms that relyexclusively on private (bank) debt. In particular, firms with bond ratings follow a traditionalLintner (1956) style dividend smoothing policy, where the influence of the prior dividendpayment is very strong and the current dividend is relatively insensitive to current eamings.In contrast, firms w ithout bond ratings flow through more of their eaming s as dividends anddisplay very little dividend smoothing behavior. In effect, they seem to follow a residualdividend policy.I. Introduction

This paper examines the interaction between the firm's debt decision and itsdividend policy. We show that the type of corporate debt a firm has outstand-ing (bank debt or pubhc debt) plays an important role in determining the firm'sdividend policy. In particular, we argue that firms that regularly access publicdebt (bond) markets are more likely to pay a dividend and subsequently followa dividend smoothing policy than firms that rely exclusively on private (bank)debt. This occurs because the use of private (bank) debt reduces the value ofthe signaling and agency reduction roles typically fulfilled by dividend paym ents.In contrast, firms with public market debt have a greater incentive to adopt div-idend policies that are designed to reduce information asymmetries and agencyproblem s in order to induce investors to hold their deb t.We address these questions by considering the dividend decisions of U.S.firms over the period 1981 to 1999. We examine the decision to pay a dividend

by analyzing a variety of fundamental firm characteristics. We then extend thesecharacteristics to include factors that cause the firm to seek public arms length

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440 Journal of Finanoial and Qu antitative Ana lysisto smooth dividends or adopt a residual dividend policy depends on public m arketaccess. To the best of our knowledge, no one has previously examined the directimpact of the decision to issue public m arket debt on a firm's dividend policy.

The paper is organized as follows. Section II discusses some fundamentalfirm characteristics and the choice between public versus private debt markets.Section III describes the data and summ ary statistics. Section IV estimates logisticregressions for predicting whether the firm pays a dividend. Section V presentsLintner coefficient estimates conditioned on firm characteristics and debt ratings.Finally, Section VI adds some conclusions and suggestions for further research.

I I . The Importance of Dividend Policy for Debt MarketsMiller and Modigliani (1961) introduced the residual theory of dividendsbased on the firm's sources and uses of funds. Based on this theory, we wouldexpect the following outcomes: firms with higher profits should pay higher div-idends; firms with higher investment rates should pay lower (or zero) dividends;firms with higher future growth opportunities should build up cash for futureinvestments and consequently make lower dividend payments; and firms facinghigher debt constraints will have less financial flexibility and thus pay lower divi-dends.While these four fundamental factors can be expected to influence the div-idend decision, they indicate little about how the firm's dividend payments areimplemented as a dividend policy. Lintner (1956) was the first to consider thiswhen he observed that firms tended to follow an adaptive process in setting theirdividend. He estimated the following equation,

/rf/,,_ 1 + /,where the actual dividend (rf/,r) was an adjustment of the existing dividend (rf/,,_ i)to the target dividend, which he hypothesized was determined by the firm's targetpayout rate and normalized eamings (e/,,). In the Lintner model, c/ is the ad-justment coefficient, a-, is a fixed time-series intercept, and , is a random errorterm.'

Lintner type dividend smoothing is normally viewed as a solution to bothagency and signaling problems.'^ However, as La Porta, Lopez de S ilanes, Shleifer,and Vishny (2000) note, financial solutions to agency problem s depend in part onthe legal environmen t and characteristics of investors. For example, dividendsmoothing may be optimal for firms with dispersed share ownership, but not for"internal" shareholders who can observe eam ings and m anagement directly. We

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Aivazian, Booth, and Cleary 441argue the same holds trae for debt markets, where the distinction is between "in-formed" private (bank) debt held by one institution and "uninform ed" pub lic mar-ket debt (bonds) with multiple investors.

The contrast between bank debt and public debt has been extensively ana-lyzed. Leiand and Pyle (1977) and D iamond (1984) both argued that banks havea comparative infonnation advantage over arms length bond m arkets. A ccordingto Diamond, this stems from the reduced monitoring costs faced by banks, whichhave better access to botb senior managers as well as confidential information thathelps alleviate signaling and agency problems. The risk to the bank is fuither re-duced by the practice of recovering the principal through monthly mortgage typepaym ents, which in effect serves a pre-comm itment function similar to a dividend.Several aspects of the bank relation serve to control agency costs and reduce sig-naling problems. It is not surprising, therefore, that James (1987) found that theannouncement of a credit facility was accompanied by a 1.7% two-day abnormalequity retum. In this sense, initiating a bank relation divulges information to thecapital market in the same way as the initiation of a dividend.

In contrast to bank debt, public bond markets are dominated by dispersedinstitutional investors. Data on bond holdings for 1990 and 1999 (not reportedhere) suggest that bonds are important assets for institutions with long-term lia-bilities. For example, in 1990 approximately 62% of all outstanding bonds wereheld by insurance companies, savings institutions, retirement funds, and privatepension funds. By 1999, this share had dropped to 47%, mainly due to an increasein foreign ho ldings from 12.7% to 18.0% and of bond funds from 3 .5% to 8.1 % .The fact that the bond market is an institutional market has important implica-tions for the criteria used to buy bonds since as fiduciaries such institutions areheavily regulated to ensure that they can meet their liabilities. ^ A common featureof these regulations is an attempt to define a set of investments that pass a "rea-sonableness" test, which reduces the legal liability of a purchaser to chiirges ofbeing "imprudent." O ne of the tests of prudence that has historically been appliedinvolves examining whether a debt issuer in question regularly pays a dividend.This suggests that a firm's dividend policy may have important implications forthe institutions that dominate the corporate bond market.

The discussion above indicates that there are significant differences betweenprivate informed debt markets and public uninformed debt markets, but how dofirms choose between them and where does dividend policy fit in? Berlin andLoeys (1988) argue that the choice hinges on the tradeoff between the relative ef-ficiency of liquidation and rescheduling versus information acquisition and mon-itoring costs. Similarly, Chem manur and Fulghieri (1994) focus on the longertime horizon of banks and their reputation incen tive to avoid incorrect liquidation

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442 Journal of Financial and Quan titative Analysisrisk, more profitable firms with fewer growth prospects are more likely to issuepublic market debt, where they also have access to longer term funds.

This discussion points to a strong interaction between dividend policy andthe type of debt issued by a firm. We have already indicated that profitable firmswith spare debt capacity and low growth opportunities (which is often proxied bythe market-to-book (M/B) ratio) are more likely to pay dividends. The discussionof debt market access above indicates that these firms are likely to issue publicmarket debt provided they are also low risk. We argue that small firms with highM/B ratios and few tangible assets are riskier than larger firms with low M/Bratios and a higher proportion of tangible assets. All three factors point towardpublic market access for larger firms with low M/B ratios and lots of tangibleassets.''

We argue that the firms most likely to pay a dividend are also likely to accessthe public debt markets if they are larger and have more tangible assets. In thiscase, they are also m ore likely to follow a Lintner style dividend smoothing policy.In contrast, firms that are unlikely to pay dividends are more likely to seek out thelower rescheduling risks attached to informed bank debt if they are also smallerwith few tangible assets. H owever, if these firms do pay a dividend they are m orelikely to follow a genuine residual policy since there is little need for them tosmooth their dividends. This is because the use of bank debt reduces the need forsignaling and mitigates agency costs, two of the main functions typically servedby dividends that lead to a smoothed dividend policy.

We identify the firm's choice between public and private debt by referringto whether the firm has a bond rating. Obviously, all firms have some form ofa banking relation since at a minimum they need check clearing and short-termborrowing facilities. However, firms without public market access need not paythe fees or provide the information required for a bond rating .

III. Sample CharacteristicsWe use annual dividend data collected for the 1981 to 1999 period from theResearch Insight (U.S. Compustat) database. All available firm-year observationswere collected and deletions were made only if the value for either total assets orsales were zero. The result is an unbalanced panel since there was no requ irementthat data be available for each firm throughout the entire period. We end up withan unusually comprehensive data set with a total number of 127,516 firm-yearobservations from all SIC industry groups. Approximately 39% (or 49,300) ofthese observations involved a firm that made a dividend payment.

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Aivazian, Booth, and Cleary 443bond ratings of which 94 % or 8,225 paid a dividend. If we think in terms of con-ditional probabilities, while the overall probability of a firm paying a dividend isabout 39%, conditional on the firm having a bond rating the probability increasesto 67% and conditional on an investment grade bond rating it increases further to94%. This evidence strongly suggests the dividend decision is closely related tothe bond rating.^

Table 1 provides summary statistics on dividend policy and other key finan-cial measures for our two time periods, 198 1-1999 and 1985-1999. The firstobservation in each row is the mean and the second the median, since accountingratios are often highly skewed. We report ratios for total common share dividendsscaled by eamings before interest and taxes (EBIT), which we term the "over-all" dividend payout, as well as by net income, which is the normal or "regular"measure of payout. We chose to scale dividends by both EBIT and net incometo avoid the influence of extra-ordinary items. For the entire sample, the averageoverall payout was 10.2% and the regular payout 26.1%, with medians of 0% forboth indicating the skewed nature of dividend payments. When the zero dividendobservations were removed, the average values increased to 26.3% and 67.4%respectively, with medians of 18.2% and 33.2%.For the period since 1985 where bond ratings are available, the median pay-out ratios for rated firms are 11.0% and 19.4% for the overall and regular payouts,

which increase to 19.9% and 37.5% for the firms that pay a dividend. In contrast,the median overall and regular payout rates for non-rated firms are both zero,while for the non-rated, dividend paying firms the medians increase to 17.9% and31.5%. This evidence suggests that while non-rated firms are less likely to pay adividend, those that do pay a dividend seem to have similar payou ts to rated firms.Similarly, if we look at the differences between investment and non-investmentgrade rated firms, we see that the differences are less pronounced for firms thatpay a dividend.^

Table 1 also provides summ ary data on several independent control variablesthat will be used in our future analysis. As hypothesized in the previous section,the m edians indicate that rated firms tend to be much larger in terms of both salesand assets, more profitable, more indebted , and tend to have more tangible assetsand lower investment rates with similar M/B ratios. When contrasting investmentversus non-investment grade firms, we see that investment grade firms are larger,more p rofitable, far less indebted, and they invest less. W hile they also have moretangible assets and higher M/B ra tios, the differences are not very pronounced.We decompose our sample into seven broad industry groups based on SIC

codes. As one would expect, this process reveals the importance of industry in-

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444 Journal of Financial and Quantitative AnalysisTABLE 1

Summary Statistics: Overall SampleFirst observa tion is the mean, the second is the m edian, Ali observations are 198 5-1999, excep t for the first two rows wh ichare for 1981-1999. Div/EBIT is dividends divided by earnings before interest and taxes; DPS/EPS is the reguiar dividendpayout; profit is net income before extraordinary items divided by totai assets; invest is capitai expenditures divided bylagged net fixed assets; debt ratio is totai debt divided by total assets; and tangibility is net fixed assets divided by totaiassets.

Totai sam pieN= 127,516

Totai sampie (positive DPS)N = 49,300

Rated firmsN = 18,675Rated firms (positive DPS)

N- 12,452Non-rated firms

N = 85,547Non.rated firms (positive DPS)

N = 25,429Investment grad e firms

N = 8,748Investment grade firms (positive DPS)N = 8,221Non-investment grade firmsW = 9,924Non-investment grade firms(positive DPS)

N = 4,227

Div/EBIT0.1020.0000.2630.1820.1790.1100.2680,1990,0860.0000.2880.1790.2540.2140.2710.2240.1120.0000.2630.135

DPS/EPS0.2610.0000.6740.3320.4290,1940.6440.3750.2070.0000.6970.3150.5190.3940.5520.4160.3510.0000.8230.253

TotalSales$mil.1,008652,25132 63,9231,1755,1581,763

45 0391,2281586,5232,3596,6812,4101,6326042,201897

TotalAssets$mil.1,954764,58246 18,4581,778

11,6132,94879 247

2,32425 015,3654,12715,7604,165

2,3667873,5581,302

Profit%- 1 4 . 22.34

5.624.351.702.873.743.67

- 2 0 . 31.706.324.384.594.234.634.31

- 0 . 0 91.712.042.60

fvlar!

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Aivazian, Boo th, and Cleary 445debt markets rather than use private bank debt, and will therefore have a bondrating. Hence, we have two testable hypotheses that can be tested em piricallyusing logistic regression models to: i) estimate the probability of a firm paying adividend; and, ii) estimate the probability of a firm possessing a debt rating. Theresults from estimating various versions of these logit models are presented inTable 2. In each case, the estimates are based on robust standard erro rs, estimatedassuming independence across firms, but not necessarily for the within-firm ob-servations. This is done to recognize that with panel data many of the firm-yearobservations are not genuinely independent since there are multiple observationsfor the sam e firm. Note that the robust standard errors are frequently much largerthan conventional estimates so our significance tests are not infiated by the largenumber of firm-year ob servations.

TABLE 2Predicting Dividend Payments and Debt Type

The dependen t variabie for Modeis #1 tfirough #6 equals 1 for a dividend a nd 0 othenise. For Modeis #7 and # 8, tfiedependen t variable is a rating indicator for tfie period 1985-1999 (1 for a rating , 0 otfierwise ). Tfie first vaiue in eao fi row istfie ooeffioient and the second the (-statistic. The last row reports the (pseudo ) R^. The number of observations is beiowthe R^ vaiue. Ail estimates include robust standard errors where independen ce is assumed a cross firms (group s), but notwithin firm-year observations. " C) indicates significance at the 1% (5% ) ievei.

Independent Variabiefviodel #n'yp e #1 Logit

Constant 0.864- 4 1 . 5 5 "Rating indicator ( = 1 rated) 1.5543 5 . 7 3 "ProfitabiiityInvestment rateMari

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446 Journal of Finanoial and Quan titative Analysisof the jointly dependent variables must be equal. Schmidt and Strauss (1975) de-veloped the simultaneotis logit model with this constraint, where both dependentvariables, similar to ours, are either 1 or 0. However, Koo and Janowitz (1983)in an application of Schmidt and Strauss's model confirm Guilkey and Schmidt's(1979) result that "very little is gained going from a single equation logit to asimultaneous logit estimation when the sample size is large (greater than 500)." ^In our case, the sample size is never less than 14,000 observations. Consequently,we implement our estimates using the single equation logit model, which has theadded benefit of allowing m ore robust specifications of the error term. ^

The results presented in Table 2 for the simplest model (#1) examine w hethera firm's likelihood of paying a dividend is influenced by whether the firm has abond rating. The coefficient on the bond rating indicator is 1.554 with a f-statisticof 35.73 (without the robust standard errors adjustment the f-statistic would havebeen 90.18). Although the pseudo R ^ value is only 6.4%, there is clearly a relationbetween the dividend decision and whether the firm has a bond rat in g. ' Model #2adjusts Model #1 to account for industry effects by including indicator (dummy)variables for each ofth e seven SIC groups discussed in Section III, where the firstis automatically dropped. Note that the pseudo R^ increases to 13.31%, but evenwith significant SIC indicators, the coefficient on the rating indicator is largelyunchanged.The period 1981 to 1999 includes a variety of econom ic conditions. Regard-less of the fundamental determinants of dividend policy we would expect divi-dends to be cut in bad rather than good economic cond itions. Model #3 in Table 2accounts for this by including annual indicator variables. Again, even though allof these indicator variables are significant, the coefficient on the rating indicator islargely unchanged . Finally, many of the later year dum mies are significantly neg-ative indicating a trend toward decreasing dividend paym ents, consistent with thework of Fama and French (2001). Model #4 controls for this trend by includingtime as an independent variable. Once again the coefficient on the rating ind icator

is largely unchanged, but we confirm the Fama-French result that the probabilityof a firm in the Compustat database paying a dividend has decreased over time.We now consider the effects of firm characteristics refiecting the residualtheory of dividends: profitability, investment rates, the M/B ratio, and the debtratio. These estimates are provided in the column for Model #5 in Table 2. Theresults show that the probability of a firm paying a dividend increases with itsprofitability and decreases with its M/B ratio and with its debt ratio with the co-efficient on the investment rate being insignificant. These results provide broad

support for the residual theory of dividends with all coefficients being of the ex-pected sign. The impact of public market access is tested in Model #6 , which

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Aivazian, Boo th, and Cieary 447markets. In comparing M odels #5 and #6, it is clear that while the coefficients onprofits, investment rate, M/B, and debt ratio do not materially change, the signson both size and the tangibility of the firm's assets are positive and highly signif-icant.' Larger firms with tangible assets are much more likely to pay a dividendthan smaller firms with more intangible assets.

A m ore explicit test of whether size and the tangibility of assets affect accessto the public debt markets is to examine whether these two variables affect theprobability of a firm having a bond rating. Model #7 in Table 2 presents the re-sults from estimating a logit model predicting whether the firm has a bond ratingusing the four fundamentals: profit, investment rate, M/B, and debt ratio. Model#8 then adds size and tangibility. Since bond ratings are only available for theperiod 1985 -1999 , the number of observations is reduced. Model #7 suggeststhat more profitable firms with high debt ratios have bond ratings. This differsfrom the results for the dividend decision reported in Models #5 and #6 where ahigh debt ratio reduced the probability of a firm paying a dividend. Neither theinvestment rate nor the M/B ratio is significant in either model. When the sizeand tangibility variables are added (i.e.. Model #8), the pseudo R ^ jumps dramati-cally, and we observe that the size variable is overwhelm ingly the most im portantexplanatory factor affecting the rating decision, with the tangibility coefficientbeing insignificant. The coefficient on debt remains significantly positive, whilethe size of the profitability coefficient is reduced substantially, and the coefficienton this variable is no longer significant. Overall, it is clear that larger firnis withmore debt seek out public debt markets, while the importance of profitability,investment rates, M/B, and asset tangibility are less important.

V. Dividend SmoothingThe results above indicate that the debt and dividend decisions are affectedby similar underlying firm characteristics and that the type of debt matters. Wenow examine whether firms with public market debt are more likely to follow asmoothing or a residual dividend policy. We address this issue by estimating thestandard Lintner m odel, which is specified in equation (1).Table 3 provides estimates for different econometric specifications of theLintner model. The first model includes all firm-year observations where we ob-tain the now standard result that, relative to Lin tner's results, the coefficient on thelagged dividend has increased to about 0.90, while that on eamings has dropped

marginally to about 0.14. We obtain this result whether we include all observa-tions or restrict the sample to positive dividend paying observations only. The

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448 Journal of Financial and Quan titative AnalysisDew enter and Warther, are puzzling since they imply equilibrium payouts of over100%." Clearly an equilibrium payout of this magnitude is a puzzle.

TABLE 3Lintner Model Regression Estimates

The dividend per share at time ((DPSj) is regressed against the lagged dividend and earnings per share vith andwithout an interaction indicator variable con structed as the rating indicator variable times the iagge d dividen d. For eachregression, the first is over ail observations inciuding zero dividend observations and the second over positive dividendpaym ents oniy. In each ca se, the first row is the coefficient on the independ ent variab ie and the secon d the (-statistic.Time period is 1981-1999 for aii observations and 1985-1999 for the subset with bond ratings. The adjusted R^ is theoverail R^ not that estimated from the fixed effects m odel; as such it is a simpie squared correlation coefficient and doesnot represen t the expiained varianc e. The significan ce of the interaction terms is given by the (-statistic. " (") indicate ssignificance at the 1% (5%) level.

Totai sampie (1981 -1999)

SiC & year indicators

Fixed effects: firm indicators

Fixed effects & autoregression (FE&A)

Rated DPS interaction (FE&A)

Rated DPS & EPS interaction (FE&A)

No.ofObs.127,51646,707

127,51646,706

127,51646,707

110,09240,234

110,09240,234

110,09240,234

Constant14.551.1813.862 0 . 2 2 "40.690.3538.790.01

131.076 . 1 3 "301.796 . 1 4 "153.97 . 9 3 "349.17 . 8 4 "159.28 . 4 6 "384.6

8 . 8 6 "

D P S , _ ,0.8941 2 . 2 9 "0.89210 .68 "0.89412 .30 "0.89210 .69 "0.7613 0 6 . 1 0 "0.8392 3 2 . 3 0 "0.6192 0 4 . 0 8 "0.678133 .22 "

- 0 . 1 3 6- 2 0 . 6 1 "- 0 . 0 3 1- 3 . 0 2 "- 0 . 3 1 6- 4 3 . 8 9 "- 0 . 2 3 8

- 2 1 . 3 5 "

EPS,0.1383 . 9 5 "0.1763 . 0 5 "0.1383 . 9 5 "0.1763 . 0 5 "0.120108 .29 "0.1608 8 . 1 8 "0.124104 .19 "0.1618 2 . 2 9 "0.117108 .83 "0.1548 6 . 6 1 "0.248117 .99 "0.265

8 5 . 1 4 "

DPSRatingInteraction

0.850131 .77 "0.7848 3 . 1 1 "1.064152 .68 "1.010

9 5 . 1 8 "

EPSRatingInteraction

- 0 . 1 6 8- 7 1 . 5 8 "- 0 . 1 5 6- 4 2 . 5 0 "

OptimalPayout

> 100%

> 100%

50.2%99.0%31.0%50.0%40.9%62.3%32.1%48.0%

Adj.(%)

81.487.981.487.981.487.982.488.374.082.974.882.2

The problem with the prior results, like those in the existing literature, is thatthey are based on panel data estimates with no prior screening or smoothing ofthe data. Consequently, they have two possible econometric weaknesses: they donot adjust for any possible dependence of firm-year observations within a group,or for any possible autocorrelation across tim e. The third model corrects for indi-vidual firm effects and the estimates are closer to those of Lintner with a sm allercoefficient on the lagged dividen d.'^ The overall model implies an equilibriumpayout of about 50%, and when estimated over nonzero dividend observations

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Aivazian, Boo th, and Cleary 449the payout is still almost 100%. The estimates from the fourth model allow con-stant autocorrelation across the individual firm observa tions, as well as fixed firmeffects.'^ For this model, the coefficient on the lagged dividend is smaller stilland the equilibrium payout is no longer unreasonable. For all observations, theequilibrium payout is 31 %, which is close to the average reported in Table 1. Asexpected, the equilibrium payout increases once the sample is restricted to onlypositive dividend paying observations, with the 50% estimate falling between theaverage and median payout ratios reported in Table 1. The results of the fourthmodel seem the most reasonable since they adjust for the possible econometricproblems associated w ith unbalanced panel data with autocorrelated e rro rs .' ' '

The fifth model in Table 3 extends the Lintner estimates to include an in-teraction term for whether the firm is rated. The interaction term is equal to thelagged dividend times an indicator variable, which is 1 if the firm is rated and 0otherwise. This is equivalent to estimating two separate regression models, whilepooling the observations to maximize the power of the tests and forcing a com-mon intercept. The simple null hypothesis is that the indicator variable for a bondrating is insignificant and that all firms smooth their dividends to the same de-gree. In this case, the interaction term should be insignificantly different from 0.However, this is not the case. For all observations, the interaction term is highlysignificant at 0.85 and the coefficient on the lagged dividend drops to -0.136.This means that non-rated observations have a negative coefficient of -0.136,while rated firms have a positive coefficient of 0.714 (i.e., 0.850 - 0.136). Thisindicates that rated firms smooth their dividends, while non-rated ones do not.For the rated firms, the equilibrium payout is 40.9%, which is an increase fromthe 31 % of the fourth model. For the positive dividend observations, the resultsare very much the same. The coefficient on the interaction term is highly signif-icant (0.784) while that on the lagged dividend is marginally negative (0.031).Again this indicates the absence of dividend smoothing by non-rated firms andvery significant smoo thing by rated firms with an equilibrium d ividend payout of62.3%.If only rated firms smooth their dividends, what happens to their payout fromcurrent operations? To answer this, we include an interaction term for eamingsequal to the earnings per share times the rating indicator. This allows both thecoefficient on the lagged dividend and the eamings to vary depending on whetherthe firm is rated, and this is the sixth m odel in Table 3.

First, notice that the impact on dividend smoothing is even more dramaticthan for the fifth model. For all observations, the coefficient on the lagged divi-dend is 0.316, while the interaction indicator for the dividend increases to 1.064,indicating an even larger impact on dividend smoothing between rated and non-

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450 Journal of Financial and Quantitative Analysisthe dividend to current eam ings . However, the interaction term is significantlynegative at 0.168, indicating that rated firms adjust their dividend much moreslowly in response to increased eamings. When the model is run only on positivedividend payments, the results are the same: highly significant interaction termsindicating that rated firms smooth their dividends more and adjust their dividendsmore slowly to increased e am ings.

The results for the sixth model are impressive; they are also entirely con-sistent w ith Lin tner's classic results, and differ from more recent results. '^ Inparticular, the statistics in Table 1 demonstrate that firms with bond ratings tendto be larger, more profitable, have more tangible assets, more debt, and lower M/Bratios than the typical firm-year observation in our sample. By all objective yard-sticks, these firms are closer to the limited sample analyzed by Lintner. For theserated, dividend paying firms, the coefficient on lagged dividends is 0.763 and thaton eamings is 0.109, implying an equilibrium payout of 4 8 % . For these firms,the Lintner model works as well as it did for Lintner. In contrast, for non-ratedfirms the coefficient on lagged dividends is 0.238 and that on eamings is 0.265.These non-rated firms seem to be following a residual dividend policy, flowingthrough a greater share of current eamings in dividends, as well as ignoring theprior period's dividend payment. Clearly these non-rated firms are not using div-idends extensively to reduce signaling and agency problems and seem to have noequilibrium dividend payout.How robust are these results? The second model in Table 3 includes SICand year dum mies so that the results are robust to industry effects. Further, whenthe fundamental firm characteristics are included as independent variables in thelogit models in Table 2, the most consistently significant variable is size. Table4 presents estimates for the Lintner model with the preferred econometric speci-fication: fixed effects with autocorrelated errors estimated over nonzero dividendpaym ents. In this case, the Lintner model is estimated over five size quintilesbased on total assets. Since the num ber of firm-year observations within eachgrouping varies, the actual number of observations in each quintile differs. Themodels are estimated both with and without interaction effects for dividends andeamings.

The estima tes in Table 4 offer several insights. First, since we know that sizeis important in both the public market access dec ision and the dividend decision, itis not surprising that the proportion of firms with a bond rating increases with size.In fact, the percentage of firms with a bond rating increases dramatically fromjust 0.3% of firms in the smallest size quintile to 60.4% in the largest quintile.Consequently, we can expect the interaction terms to be more significant for largerfirms, which they are. Second, the Lintner model only has "normal" coefficients

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Aivazian, Booth, and Cleary 451TABLE 4

Size and Lintner Model Regression EstimatesThe dividend per share at time ((DP S,) is regressed against the lagged d ividend a nd earnings per share with and withoutthe interaction variabie. Ail modeis are estimated as fixed effects with first order autoregression correction (FE & AR).The modeis are estimated over positive dividend observations only for five quintiies based on totai assets, with TA1 thesmaiiest to TA5 the largest quintiie. For each regression , the first row is the coefficient on the indepen dent variable an d theseco nd the (-statistic. Note in the autoregression correction one observation for each firm is dropped since iarger firmstend to have more time-series observations. The effective sampie size of the totai asset quintiies increases with size. " (*)indicates significance at the 1 % (5%) ievei.

F E & A R FE & AR with interaction

Overali sampieTA1TA2TA3TA4TA5

No .ofObs.40,2236,795

7,064

7,248

7,708

8,498

%Rated25.0

0.34.7

19.841.060.4

D P S , _ i0.677133 .2 "0.1342 7 . 4 "

- 0 . 0 7 3- 1 0 . 3 7 "- 0 . 3 0 6- 2 6 . 9 8 "

0.14516.47"0.7416 9 . 2 0 "

EPS,0.1618 2 . 2 9 "0.817109 .6 "

- 0 . 0 0 0- 0 . 0 50.4933 0 . 6 9 "0.5254 7 . 2 0 "0.1614 0 . 6 8 "

D P S , _ ,- 0 . 2 3 8- 2 1 . 3 5 "

0.1332 7 . 5 "- 0 . 0 7 2- 1 2 . 2 9 "- 0 . 3 3 0- 2 7 . 6 5 "0.22317 .52 "

- 0 . 4 1 9- 1 6 . 1 9 "

EPS,0.2658 5 . 1 4 "0.817109 .6 "0.6975 2 . 6 1 "0.6042 5 . 9 4 "0.63234 .24 "0.2794 4 . 7 4 "

DPSRatinginteraction

1.0169 5 . 1 8 "0.4790.300.0926 . 7 5 "0.6277 .49 "

- 0 . 2 9 6- 1 7 . 5 9 "1.1784 9 . 0 8 "

EPSRatingInteraction- 0 . 1 5 64 2 . 5 6 "- 0 . 3 7 0- 0 . 2 7- 0 . 6 9 9- 5 2 . 8 0 "- 0 . 1 9 7- 6 . 6 7 "- 0 . 1 3 8- 6 . 8 7 "- 0 . 1 8 2- 2 4 . 4 3 "

largest where it is prob lematic given the negative sign on the lagged dividend. Asone would expect, dividend smoothing is most apparent for the largest finns withbond ratings and with the greatest access to public debt markets.The results based on panel data after adjusting for both autoregressive residu-als and dependence across firm observations are consistent with Lintner's results,and are also consistent with the reported summary statistics in Table 1. In con-trast with other recent work, the equilibrium payout estimates also make sense.Further, these results are also broader than L intner 's since the estimates are drawnfrom a broader array of firms. What is quite clear is that the extent of dividendsmoothing depends on whether a firm has a bond rating. We find very little evi-dence that firms without a bond rating smooth their dividends. In fact, quite theopposite, larger dividends tend to be followed by smaller dividends and vice versa,as firms fiow through a much larger share of their current eamings (about 25%)into dividends. In contrast, there is very strong evidence that firms with bond rat-ings smooth their dividends since their dividends are adjusted much more slowlyin response to current eamings. This is consistent with our prediction that firms

with bond ratings smooth their dividends as part of a strategy to maintain accessto public bond markets. The fact that this result is strongest for the largest firms

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452 Journal of Financial and Quan titative Analysisdebt, but the type of debt. Firms tbat access public debt markets are larger firmswith more tangible assets and lower M/B ratios, and tend to pay dividends. Thebond rating aggregates this information into a single variable, which empiricallyserves to differentiate dividend policy. Lintner style dividend smoothing seemsprimarily a solution to agency and signaling problems only for larger firms withbond ratings. It is these types of firms that have to deal with dispersed publicbond market investors. In contrast, firms without bond ratings borrow from theprivate bank market, and have little reason to use dividend policy to solve agencyand information prob lems. Hence, these firms follow a residual dividend policy.

Empirically, we find support for the above propositions by running Lint-ner style regressions that include interaction terms related to whether a firm israted. The regression results provide very strong evidence that firms with bondratings smooth their dividends and pay out less from current earnings than firmsthat are not rated. In particular, the signs on the interaction terms are very largeand overwhelmingly significant, demonstrating that rated firms smooth their div-idends whereas non-rated firms do not and, instead, follow a residual dividendpolicy. Moreover, tbe equilibrium payout from these augmented Lintner modelsis consistent with traditional estimates (and our summary statistics), suggestingan overall equilibrium dividend payout of about 50%.Our preliminary tests also confirm that the probability of a firm paying a

dividend increases with the firm's profitability and decreases with the finn's debtlevel and the existence of high future growth opportunities. These tests also con-firm that the probability of a firm paying a dividend has declined over time, con -sistent with the recent work of Fama and French (2001). In order to examineour hypotheses, we then include two proxies for public debt market access in ourlogit regressions and find that size is overwhelmingly significant in determiningwhether a firm pays a dividend while asset tangibility is also important.We also estimate directly the factors that influence the probability of a firmhaving a bond rating, and find that this probability is strongly associated with thesame set of fundamental factors that influence the likelihood of paying a dividend,and that public market access proxies (size and asset tangibility) are the mostimportant. In particular, we find that large, profitable firms w ith tangible assetsand low M/B ratios tend to obtain bond ratings. The only obvious difference,as compared to the dividend models, is that firms with high debt tend to alsohave bond ratings whereas high debt firms have a lower probability of paying adividend. Clearly if firms do not have much debt outstanding it makes little senseto access public markets and obtain a bond rating. All of our results are robust

to the inclusion of industry controls that account, for example, for the specialcircumstances of regulated industries.

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Aivazian, Boo th, and Cleary 453Diamond, D. W. "Financial Intermediation and Delegated Monitoring." Review of Econom ic Studies,51 (1984), 393^14.Easterbrook, F. H. "Two Agency-Cost Explanations of Dividends." American Economic Review, 74(1984), 650-6 59.Fama , E., and H. Bab iak. "Dividend Policy: An Emp irical Ana lysis." Journat of the AmericanSlatisticat Association, 63 (1968), 1132-1161.Fama, E., and K. French. "The Cross Section of Expected Retums." Journal of Finance, 47 (1992),427-465.Fama, E., and K. French. "Disappearing Dividends: Changing Firm Characteristics or Lower Propen-sity to Pay?" Journal ofFinanciat Economics, 60 (2001), 3-4 3.Graham, J., and C. Harvey. "The Theory and Practice of Corporate Finance: Evidence from the Field."Journal of Financiat Economics, 60(2001), 187-243.Guilkey, D., and P. Schmidt. "Some Small Sample Properties of Estimators and Test Statistics in theMultivariate Logit Model." Journat of Econom etrics, 10 (1979), 33-42 .James, C. "Some Evidence on the Uniqueness of Bank Loans." Journat ofFinanciat Economics, 19

(1987), 217-235 .Kisgen, D. "Credit Ratings and Capital Structure." Working Paper, Boston College (2004).Koo, H., and B. Janowitz. "Interrelationships between Fertility and Marital Dissolution: Results of aSimultaneous Logit Model." Demography, 20 (1983), 129-145.La Porta, R.; F. Lopez de Silanes; A. Shieifer; and R. Vishny. "Agency Problem s and DividendPolicies Around the World." Journat of Finance, 55 (2000), 1-33.Lintner, J. "Distribution of Incomes of Corporations among Dividends, Retained Eamings and Taxes."American Economic Review, 46 (1956), 97-1 13.Leiand, H., and D. Pyle. "Information Asymmetries, Financial Stmcture and Financial Intermedi-aries." Journat of Finance, 32 (1977), 371-38 7.Miller, M., and F. Mo digliani. "Dividend Policy Growth and the Valuation of Shares." Journat ofBusiness, 34 (1961), 41 1^ 33 .Rajan, R. "Insiders and Outsiders: The Choice between Informed and Ami's Length Debt." Journatof Finance, 47 (1992), 1367-1400.Schm idt, P., and R. Strauss. "Estim ation of M odels with Jointly Depe ndent Q ualitative V ariables: ASimultaneous Logit Approach." Econometrica, 43 (1975), 745-75 5.

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