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Index

1.Introduction.................................................................................................................3

2.Data description...........................................................................................................5

3.Empirical tests.............................................................................................................7

3.1 Capital structure and company value....................................................................7

3.2 Robustness ..........................................................................................................13

4. Conclusion and discussion....................................................................................13

5. References .............................................................................................................14

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1.Introduction

One of the cornerstones of the modern corporate finance theory is the capital structure

irrelevancy proposition (Modigliani-Miller 1958). Modigliani and Miller (1958)

conclude that the market value of any firm is independent of its capital structure,

given the assumptions of capital markets are perfect, which means arbitrage-free,

competitive and efficient, no tax distortions and no bankruptcy. After tax is

introduced into their model, tax shield and bankruptcies costs add more complications

to the optimal capital structure decision-making process. It is observed that the

optimal capital structure are closely related to the growth potential of the firms

(McConnel & Servaes1995; Jung, Kim, & Stulz 1996) and some other variables, such

as: the size and the industry characteristics (Titman & Wessels1988). In this paper, wewill try to empirically test the influence of the debt structure on the company value

given different growth opportunities with the companies incorporated in the

Netherlands.

Debt policy and equity ownership structure matter and that the way in which they

matter differs between firms with many and firms with few positive net present value

projects (McConnel & Servaes). Leland & Pyle (1977) and Ross (1977) propose that

managers will take debt/equity ratio as a signal, by the fact that high leverage implies

higher bankruptcy risk (and costs) for low quality firms. Since managers always have

information advantage over the outsiders, the debt structure may be considered as a

signal to the market. Rosss model suggests that the values of firms will rise with

leverage, since increasing leverage increases the markets perception of value.

Suppose there is no agency problem, i.e. management acts in the interest of all

shareholders. The manager will maximize company value by choosing the optimal

capital structure: highest possible debt ratio. High-quality firms need to signal their

quality to the market, while the low-quality firms managers will try to imitate.

According to this argument, the debt level should be positively related to the value of

the firm.

Assuming information asymmetry, the pecking order theory (Myers and Majluf,

1984) predicts that firm will follow the pecking order as optimal financing strategy.

The reason behind this theory is that if the manager act on behalf of the owners, they

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will issue securities at a higher price than they are truly worth. The more sensitive of

the security, the higher the cost of equity capital, since the action of the manager is

giving a signal to the market that the securities is overpriced.

Stulz (1990) argues that debt can have both a positive and negative effect on the value

of the firm (even in the absence of corporate taxes and bankruptcy costs). He develops

a model in which debt financing can both alleviate the overinvestment problem and

the underinvestment problem. Stulz (1990) assumes that managers have no equity

ownership in the firm and receive utility by managing a larger firm. The power of

manage may motivate the self-interest managers to undertake negative present value

projects. To solve this problem, shareholders force firms to issue debt. But if firms are

forced to pay out funds, they may have to forgo positive present value projects.Therefore, the optimal debt structure is determined by balancing the optimal agency

cost of debt and the agency cost of managerial discretion.

Building on the argument that high-growth firms corporate value is negatively

correlated with leverage, whereas for lowgrowth firms corporate value is positively

correlated with leverage (McConnell & Servaes, 1995), we should observe that the

growth opportunities may influence the optimal capital structure. The reason is that

the optimal leverage may shift with the changes of growth opportunities that lead to

the changes of agency costs of debt and cost of managerial discretion (Jung, Kim,

Stulz. 1996). Assuming that the managers are self-interest, the growth opportunities of

the firm may be positively related to the level of the goal congruent of the firm and its

manager, therefore negatively related to the cost of managerial discretion (Jung, Kim,

Stulz. 1996). On the other hand, the agency cost of debt is positively related to the

growth opportunities.

According to Stulz (1990), McConnell & Servaes (1995), Jung, Kim, Stulz (1996),

the influences of the debt on the firms value depending on the presence of growth

opportunities. For firms facing low growth opportunities, the debt ratios are positively

related to the firm value. For firms facing high growth opportunities, the debt ratios

are negatively related to the firm value.

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and multiplied by 100), Tax Rate (the sum of Income Taxes divided by the Pre-tax

Income less Appropriations to Untaxed Reserves and multiplied by 100), Total

Capital Expenditures, Total Current Liabilities, Total Long Term Debt, and Total

Assets.

Table 1 reports the descriptive statistics of our sample. The mean price-to-earnings

ratio, P/E, is 21.55, while the median P/E is 8.65. The largest P/E ratio is 449.89,

which comes from KLM-Royal Dutch Airlines. The mean current liabilities to assets

ratio and long-term debt to assets ratio is 42.12 and 11.10 respectively. In the sample

there are 11 firms has no debt at all, while 22 firms long-term debt to total assets

ratio are between zero and one per cent. Totally 25.98% of the firms in our sample

have chosen near zero debt financial structure. By construction, the Tobins Q are between 0.16 and 6, and the median of Q is 1.73. The median of our samples total

assets is 193.13 million United States Dollar, USD. The largest firm in our sample is

ROYAL DUTCH PETROLEUM NV, whose total assets book value is 36,184.10

million USD.

Table 1

Descriptive Statistics

PE TQ PM TR CE TC TL TAMean 21,55 2,12 3,81 31,04 7,17 42,12 11,10 1741,05

Median 8,65 1,73 4,61 32,47 6,50 40,03 7,49 193,13Maximum 449,89 5,80 100,25 226,75 29,41 78,76 57,38 36184,10Minimum -17,27 0,18 -169,39 -14,82 0,00 5,16 0,00 4,11Std. Dev. 61,29 1,36 23,84 28,96 4,98 16,45 12,12 5236,88Skewness 6,06 0,87 -4,31 4,39 1,47 0,07 1,20 5,43Kurtosis 41,42 2,82 35,94 29,13 6,28 2,61 4,11 34,67Obser. 112 112 112 112 112 112 112 112

Definition of the variables :PE: Price to Equity ratioTQ: Tobin's Q, Market to book ratioPM: Pre-tax Profit MarginTR: Tax RatCE: Capital Expenditures to Total Asset

ratioTC: Current Debt to Total Asset ratioTL: Long-term Debt to Total Asset ratioTA: Total Assets

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3.Empirical tests

3.1 Capital s t ruc ture and co mp any value

McConnell and Servaes (1995) conjecture that the correlation between Tobins Q and

leverage will be negative for high-growth firms and positive for low-growth firms.

They employ samples of 1173 firms in 1976, 1093 firms in 1986 and 830 firms in

1988, which are listed on the New York Stock Exchange or American Stock

Exchange, and use P/E ratio to differentiate the sample to high-growth subsample and

low-growth subsample. They find evidence to support their conjecture.

Follow their methodology, we use P/E ratio to differentiate our sample. Firms are

ranked according to their P/E ratio. The one-third of the firms with the highest P/E

ratio is placed into a high-growth sample, and the one-third with the lowest P/E ratio

is placed into a low-growth sample. Thus there is a high-growth sample of 42 firms

and a low-growth sample of 42 firms. Table 2 presents the summary statistics of

subsamples.

Table 2

Summary statistics of subsamples

Low- High- P ValueGrowth Growth of Diff.

PE Mean 2,30 53,60 0,00 Median 5,67 18,81 0,00

TQ Mean 1,51 2,67 0,00 Median 1,10 2,29 0,00

PM Mean -4,78 9,44 0,02 Median 4,80 4,33 0,24

TR Mean 29,84 35,25 0,54 Median 32,07 32,72 0,37

CE Mean 7,56 7,10 0,70 Median 7,34 6,28 0,18TC Mean 42,89 37,46 0,22

Median 41,70 38,06 0,17TL Mean 12,53 11,22 0,33

Median 8,61 4,47 0,36TA Mean 1758,56 2367,24 0,57

Median 129,35 183,50 0,88

Definition of the variables :PE: Price to Equity ratioTQ: Tobin's Q, Market to book ratioPM: Pre-tax Profit Margin

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the largest firm in our sample, Royal Dutch Petroleum NV, also choose zero debt

capital structure. Table 5 reports the descriptive statistics of this subsample. The mean

P/E ratio is 32.81, much higher than the whole sample, whose mean P/E ratio is 21.55.

The mean and median Q is 2.31 and 2.29, also higher than the whole sample, whose

value is 2.12 and 1.73 respectively. As the statistics software we used (Eview 3.0)

cant do equality test of samples with different number of observations, we cant say

whether it is significantly higher. But we think that it might be an interesting topic to

investigate.

Table 5

Descriptive Statistics of Near Zero Debt Firms

PE TQ PPM TR CE TC TL TA

Mean 32.81 2.31 9.60 26.98 6.21 39.28 0.11 1184.40Standard Error 13.78 0.25 3.48 2.69 0.94 3.46 0.04 1089.83Median 9.85 2.29 5.23 32.99 4.21 38.43 0.00 32.00Minimum -6.78 0.40 -30.05 -0.07 0.00 5.16 0.00 6.92Maximum 438.66 5.06 100.25 60.14 29.41 78.76 0.92 36046.73Sum 1082.71 76.21 316.76 890.18 204.87 1296.38 3.79 39085.19Count 33 33 33 33 33 33 33 33

In corporate governance theory, debt-discipline is part of corporate discipline

mechanism. Firms choose no debt mean that they dont want this discipline

mechanism. It will have negative impact on the company based on Ross (1977) model

since debt are positively related to the firm value in that model. A negative

consequence of long-term debt issue is the cost of disclosure. By disclosing the

financial information, firms are viable to public supervision and bankruptcy cost.

On the other hand, Stulz (1990) argues that debt can have negative effect on the value

of the firm. Managers of firms with high growth opportunities may have to forgo

positive present value projects, if firms have debt outstanding. So zero debt is good

news for high growth firms.

We add dummy variable of zero-debt to our regression (table 6). The dummy variable

of zero-debt is defined to equal one if the firms long-term debt ratio is less than one

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per cent, other wise equal zero. The dependent variable in the regression is Tobins Q.

The independent variables are zero-debt dummy, current debt to assets ratio, long-

term debt to asset, pre-tax profit margin ratio, tax rate, capital expenditures ratio, and

total assets. Our regression (table 6 regression1) result indicates zero-debt capital

structure has significantly positive impact to company value. The coefficient is 0.91,

with p-value 0.01. One problem of our regression is the dummy is correlated to long-

term debt ratio. So we run our regression again without long-term debt ratio variable

in regression 2. The coefficient of zero-long-term-debt dummy becomes insignificant

( p-value 0.33), but still positive.

Table 6

Tests the Effects of Zero Debt

Regression 1 Regression 2 Regression 3 Regression 4Low-Growth High-Growth Low-Growth

(New)High-Growth(New)

Variab. Coef. Prob. Coef. Prob. Coef. Prob. Coef. Prob. Coef. Prob. Coef. Prob.

Interc. 0.63 0.18 1.53 0.00 -0.17 0.80 0.50 0.72 -0.11 0.82 0.25 0.80TC 0.02 0.00 0.02 0.04 0.03 0.01 0.02 0.26 0.03 0.00 0.03 0.04TL 0.04 0.01 0.03 0.04 0.06 0.03 0.03 0.02 0.06 0.01TD 0.91 0.01 0.31 0.33 0.75 0.19 0.95 0.23 0.67 0.13 0.88 0.07PM 0.00 0.43 0.00 0.87 -0.01 0.19 0.05 0.20 -0.01 0.32 0.05 0.03TR -0.01 0.17 -0.01 0.09 -0.00 0.57 -0.01 0.47 -0.00 0.38 -0.01 0.45CE 0.00 0.87 -0.01 0.79 -0.03 0.54 0.03 0.34 -0.01 0.60 0.01 0.62TA 0.0000

220.23 0.0000

320.18 0.0000

320.00 -0.00

00660.43 0.0000

270.01 -0.00

00810.12

R-squa.

0.13 0.06 0.25 0.23 0.24 0.23

Adj. R-squa.

0.07 0.01 0.10 0.08 0.14 0.11

To test whether the relation between corporate value and zero-debt capital structure

differs between firms with few and those with many growth opportunities, we run

regression again with low-growth sample and high-growth sample separately (table 6

regression 3). In both samples, the coefficient is insignificantly positive. But if we

define high-growth sample as the one-half of the sample (new) with higher P/E ratios,

the coefficient becomes significantly positive (regression 4). Regression results are

reported in Table 6.

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5. References

Jung, K., Kim, Y.C., and Stulz, R.M. 1996 Timing, investment opportunities,

managerial discretion, and the security issue decision, Journal of Financial

Economics

Leland, H. E. and Pyle, D. H. 1977 Informational asymmetries, financial structure,

and financial intermediation, Journal of Finance

McConnell, J. J & Servaes, H. 1995 Equity ownership and the two faces of debt,

Journal of Financial Economics

Modigliani, F. and Miller, M. H. 1958 The cost of capital, corporation finance and

the theory of investment, American Economic Review

Morck, R., Shleifer, A. and Vishny, R.W. 1988 Management ownership and market

valuation: an empirical analysis, Journal of Financial Economics

Myers, S. C. & Majluf, N.S. 1984 Corporate financing and investment decisions

when firms have information that investors do not have, Journal of Financial

Economics

Ross, S. A. 1977 The determination of financial structure: the incentive-signalling

approach, The Bell Journal of Economics

Stulz, R. 1990 Managerial discretion and optimal financing policies, Journal of

Financial Economics

Titman, S. and Wessels, R. 1988 The determinants of capital structure choice,

Journal of Finance