Growth opportunities, capital structure and dividend policies in Japan

Ž .Journal of Corporate Finance 5 1999 141–168www.elsevier.comrlocatereconbase

Growth opportunities, capital structure anddividend policies in Japan

Ferdinand A. Gul )

Department of Accountancy, City UniÕersity of Hong Kong, Tat Chee AÕenue, Kowloon Tong,Hong Kong, China

Received 1 August 1995; accepted 1 October 1998

Abstract

This paper, using 5308 observations of listed Japanese firms between the years 1988–1992, provides additional evidence on contracting theory arguments for the relation betweengrowth opportunities, capital structure and dividend policies. To avoid the problems of

Ž .using cross-sectional proxies for time-sequenced variables, this study uses 1 pooledŽ .cross-sectional time-series analysis and 2 time-series analysis with a one-year lag for the

dependent variables. Results show significant negative relations between growth opportuni-ties and levels of both debt financing and dividend yields after controlling for firm size,profitability, firm keiretsu affiliations and industry regulation. The results are consistentwith contracting cost arguments for corporate finance and dividend policies and confirm theimportance of growth opportunities in corporate finance theory. q 1999 Elsevier ScienceB.V. All rights reserved.

JEL classification: G32; G35

Keywords: Japan; Growth opportunities; Dividends; Debt; Keiretsu

1. Introduction

An important body of research on capital structure and dividend policiesattempts to validate the theory that differences in contracting costs may provide an

Žexplanation for cross-sectional variations in these financial policies Jensen and

) Tel.: q852-2788-7919; fax: q852-2788-7944; e-mail: [email protected]

0929-1199r99r$ - see front matter q 1999 Elsevier Science B.V. All rights reserved.Ž .PII: S0929-1199 99 00003-6

( )F.A. GulrJournal of Corporate Finance 5 1999 141–168142

.Meckling, 1976; Rozeff, 1982; Easterbrook, 1984 . In particular, differences inŽ .contracting costs that arise from a firm’s investment opportunity set IOS are

expected to be related to corporate financing and dividend decisions. To date,relatively few empirical studies have addressed this issue. The studies that havebeen done have been conducted on US data, thus, providing a country-specific testof the theory.

The objective of this paper is to investigate the relationship between IOS andcapital structure and dividend policy of listed Japanese firms. The interest instudying Japan stems from three factors. First, unlike in the US, Japanese legaland regulatory environment permit commercial banks and financial institutions to

Žown shares in corporations and exert more control Jensen, 1989; Prowse, 1991,. 11992 . Second, there exist differences between keiretsu or industrial groups

centered around affiliated banks and financial institutions and unaffiliated indepen-dent firms with weaker banking ties. The differences in institutional arrangementsbetween keiretsu and non-keiretsu firms may influence the behavior of sharehold-

Ž .ers as monitors Hoshi et al., 1991; Prowse, 1992 . Third, there is evidence tosuggest that monitoring functions of large shareholders of keiretsu firms are

Ž .different from that of US firms. Kester 1990 describes the corporate governancesystem of keiretsu firms in terms of a complex interaction between shareholdings,credit holding and long-term business relationship that exist between the firm and

Ž .its stake holders. Prowse 1990, 1992 suggests that the problems of wealthtransfers from debtholders to shareholders are unlikely to exist for keiretsu firmsbecause the large shareholders are also large debtholders. The concentration ofborrowing and the linkage between debt and equity reduces the cost of financialdistress because it reduces conflicts between investors when a firm is near defaultŽ .Hoshi et al., 1991 . Thus, the unique Japanese institutional arrangements providean interesting backdrop to investigate whether contracting costs explanations fordebt and dividend policies still apply given these differences.

Much of the theoretical and empirical basis for this paper is drawn from twoŽ . Ž .related studies. Smith and Watts 1992 SW report significant associations

between IOS and capital structure and dividend policy. They use the contractingŽ .perspective to explain their findings. Gaver and Gaver 1993 extend the SW study

by conducting a cross-sectional analysis at the firm, rather than the industry leveland use an index of investment opportunities based on six proxies for growth

2 Ž .opportunities. Gaver and Gaver’s GG results are in general consistent with theŽ .findings of Smith and Watts 1992 that firms with good growth opportunities

1 In the US, the Glass–Steagall Act prohibits any equity ownership by banks.2 Ž . Ž .The proxies are 1 the ratio of firm market value to the book value of assets, 2 the ratio of

Ž . Ž .market to book value of equity, 3 the ratio of R&D expenditures to the book value of assets, 4 theŽ . Ž .earningsrprice ratio, 5 the variance of the total stock return of the firm, and 6 the frequency that the

Ž .firm is included in the holdings of growth-oriented mutual funds Gaver and Gaver, 1993 .

( )F.A. GulrJournal of Corporate Finance 5 1999 141–168 143

have significantly lower debtrequity ratios and lower dividend yields than non-growth firms.

This paper provides pooled cross-sectional time-series and ‘lagged’ time-seriesevidence on the relation between IOS and corporate finance policies for listedJapanese firms using observations for the five-year period from 1988 to 1992

Ž .obtained from PACAP Pacific-Basin Capital Markets files. The ‘lagged’ time-series is used to overcome the concern in the GG study of spurious correlationbetween debtrequity ratio and dividend yield and the IOS because each of the

Žthree proxies for the IOS market-to-book assets, market-to-book equity and. Žearningsrprice ratio is also dependent on stock price Gaver and Gaver, 1993, p.

.154 .The results show that high growth firms have significantly lower debtrequity

ratios and dividend yields compared to low growth firms, which support thefindings of SW and GG. In particular, the use of the ‘lagged’ variable approachprovides a more robust test of the theory. In addition, the study found that keiretsufirms are associated with higher debt, controlling for growth opportunities.

Section 2 provides an explanation for the relation between IOS and both capitalstructure and dividend policy and the empirical proxies for the IOS and Section 3provides a discussion of the sample selection process and characteristics of thesample. Section 4 presents the results and a discussion and summary of thefindings are provided in Section 5.

2. The relation between IOS and corporate financial policies

2.1. Growth opportunities, capital structure and diÕidend policy

Ž .Following Myers 1977 , growth opportunities are considered in terms of theproportion of firm value accounted for by assets-in-place; the lower the fraction offirm value represented by assets-in-place, the greater are the firm’s growth

Ž .opportunities or IOS. Mason and Merton 1985 point out that firms with growthoptions are those that have relatively more capacity expansion projects, newproduct lines, acquisition of other firms and maintenance and replacement ofexisting assets. Three theories that might explain the association between IOS and

Žcorporate finance policy are the tax, signaling and contracting arguments Smith.and Watts, 1992 .

An important tax argument, for example, relies on the progressivity in taxeswhich implies that expected tax liabilities are higher when there is greatervolatility in taxable income. Thus, firms with high growth options and high cashflow volatility have incentives to reduce debt in their capital structure over the

Ž .range of progressivity Smith and Watts, 1992 . This tax effect suggest a negativeassociation between IOS and debt.

The signaling hypothesis is based on the impact of information asymmetries ondebt policies. For example, firms with high growth options face greater informa-


tion disparities and therefore are expected to have higher debt levels to signalhigher quality. This signaling effect predicts a positive association between IOSand debt.

Following the contracting perspective, firms with more growth opportunitiesare less likely to issue debt for two reasons. 3 First, the underinvestment problemsuggests that firms generally issue only risky debt that can be supported byassets-in-place. If not, managers acting on behalf of shareholders may decide notto undertake positive net present value investments to avoid the possibility of thepayoffs going to debtholders. This suggests that, other things being equal, thelower the assets-in-place, the lower the financial leverage. Second, given that debthas been issued, the asset-substitution problem occurs when managers acting onbehalf of shareholders opportunistically substitute higher variance assets for lowervariance assets. In this way, wealth is being transferred to the shareholdersprovided the debt was issued and priced on the basis of low variance assets. Assetsubstitution is less likely when there are more assets-in-place since it is relativelyeasy for outsiders such as auditors to monitor the existence and value of theseassets such as land, building and plant. However, when a firm has more intangiblegrowth opportunities, asset substitution is more likely since outside monitoring ofthese assets is more difficult. Thus, firms with more growth opportunities 4 areless likely to issue debt other things being equal.

The costly contracting perspective 5 and the evidence obtained in prior studiesŽLong and Malitz, 1985; Smith and Watts, 1992; Gaver and Gaver, 1993; Goyal et

.al., 1998 suggests the following hypothesis.

H1. Firms with lower levels of growth opportunities will have more debt.

A review of the literature suggests two explanations for the association betweengrowth opportunities and dividend policy. 6 The first explanation, which relies onthe signaling perspective, suggests that high quality firms may commit to larger

Ž .dividends in order to ‘certify’ or signal to the market their higher qualityŽ . Ž .Easterbrook, 1984 . This is also consistent with the views of Bhattacharya 1979 ,who argues that high quality firms pay higher dividends to reduce informationdisparities between managers and investors of high growth firms. Thus, highdividends may be associated with high investment opportunities.

The second explanation, which relies on contracting costs arguments, suggestŽthat dividends may serve incentive roles Jensen, 1986; Milgrom and Roberts,

3 Ž . Ž .See, also, arguments by Myers and Majluf 1984 and discussion by Titman and Wessels 1988 .4 Both the underinvestment and asset substitution problems are likely to be less severe for keiretsu

firms since the large shareholders in most keiretsu firms are also debtholders.5 The lack of information on the specific tax status of the companies makes it difficult to conduct

tests of the tax hypothesis.6 Ž .Smith and Watts 1992 point out that no tax analysis exists in the dividend literature to explain

cross-sectional variations in dividends.


.1992 . Dividend payments remove resources from the firm and so help to mitigate7 Ž .agency costs of free cash flows. Milgrom and Roberts 1992, p. 507 point out

that ‘‘this incentive effect argues for dividends being higher in slow-growthindustries than ones with good investment opportunities’’. This assumes that firmswithout profitable investment opportunities will pay higher dividends than under-

Ž .take negative net present value projects Smith and Warner, 1979 . On the otherhand, firms with high growth opportunities are likely to pay lower dividends sincethey have lower free cash flows and less flexibility in their dividend policy. Thesefirms may also pay lower dividends to reduce their reliance on costly external

Ž .financing. This reasoning which has considerable support Gaver and Gaver, 1993Ž .is consistent with the interpretation by Rozeff 1982 and leads to H2.

H2. Firms with lower levels of growth opportunities have higher dividends.

2.2. IOS measure

IOS is measured in terms of three widely used proxies for growth opportunitiesŽ .Goyal et al., 1998 . The first variable is the ratio of market value of assets to

8 Ž .book value of assets French and Poterba, 1991 which is defined as follows:

wMKTBKASs Book assetsyTotal common equityqShares outstanding

x=Share closing price %Book assets. 1Ž .

This ratio is selected for two reasons. First, as argued by SW and GG, this ratiois inversely related to the proportion of firm value accounted for by assets in placeand hence directly related to the proportion of firm value accounted for by its

Ž .investments opportunities. Second, Skinner 1993 used variations of this ratio ofthe value of gross property, plant and equipment to firm value, and Tobin’s q,defined as the ratio of market value of the firm to the replacement cost of theassets. A number of recent research have used this proxy to examine the relationbetween growth opportunities and debt, dividend policy and compensation con-

Žtracts Morck et al., 1988; Barclay and Smith, 1995; Rajan and Zingales, 1995;.Goyal et al., 1998 .

7 Free cash flows is defined as cash flow in excess of that required to fund all projects that haveŽ .positive net present values when discounted at the relevant cost of capital Jensen, 1986 .

8 A possible limitation is that this measure contains potentially significant measurement errors forfirms with long-lived assets since book value is historical cost less depreciation. SW encountered thesame problem in their proxy for IOS. A redeeming factor, however, is that virtually all Japanese firmsuse accelerated depreciation.


ŽThe second measure is the ratio of the market to book value of equity Chung.and Charoenwong, 1991 which is defined as follows:

w xMKTBKEQs Shares outstanding=Share closing price

%Total book value of common equity. 2Ž .Two reasons prompt the selection of this measure. First, the difference between

the market and book value of equity approximates the value of investmentŽ .opportunities facing the firm Collins and Kothari, 1989 . Second, future earnings

that the firm is expected to produce and the expected growth rate of both earningsŽand cash flow are determined by the amount of growth opportunities Lewellen et

.al., 1987 .Ž . 9The third empirical proxy for IOS selected is the earningsrprice EP ratio

Ž .Beaver and Morse, 1978 which is defined as follows:

EPsPrimary EPS before extraordinary item%Share closing price. 3Ž .Ž .Chung and Charoenwong 1991 demonstrate that the EP ratio is inversely related

to growth opportunities; the larger the EP ratio, the larger the proportion of equityvalue attributable to earnings from assets-in-place. 10 Chung and CharoenwongŽ .1991, p. 26 also demonstrate that the EP ratio is more robust than the price–earn-ings ratio to possible distortion when a firm has earnings that is close to zero ornegative. 11

2.3. Dependent Õariables identification

Financing policy is defined in terms of the following two versions of thedebtrequity ratio:

Book debtrequity ratiosTotal book value of liabilities

%Total book value of common equity. 4Ž .Market debtrequitysTotal book value of liabilities

w x% Shares outstanding=Share closing price . 5Ž .Similarly, dividend policy is defined in terms of the following two versions: the

9 A possible limitation with the use of this measure is that many firms may use unconsolidatedŽ .earnings for reported PrE ratios French and Poterba, 1991 and Japanese tax code allow firms to set

Ž .aside funds against future contingencies including payment of retirement benefits . These factors couldreduce reported earnings and bias the EPS measure. To check for this, separate regressions are runusing only the EPS measure as a proxy for IOS and the results are qualitatively similar to the resultsobtained using the IOS index.

10 It is assumed that current earnings is an appropriate proxy for cash flows generated from assets.Ž .The ratio is only used for firms with non-negative earnings see Gaver and Gaver, 1993, p. 132 .

11 Ž .See French and Poterba 1991 for a discussion on the reasons why Japanese firms have relativelyŽ .high PE low EP ratios.


dividend payout ratio which is accounting-based and the dividend yield which ismarket-based.

Dividend payoutsDividends per share

%Primary earnings per share before extraordinary item.6Ž .

Dividend yieldsDividends per share%Price per share. 7Ž .

3. Data collection and description

3.1. Sample selection and characteristics

The sample consists of firms reported in PACAP files with no missing valuesfor the variables under investigation for the years 1988–1992. The pooledcross-section time-series data is collected for five years in the vast majority ofcases. For some firms, complete data for a particular year is not available, inwhich case no observations for that particular year is recorded. For the purpose ofthe ‘lagged’ analysis, firms that had complete data for the two relevant years areselected. In other words, data for the independent variable in say, year 1988,should be available for the same firms in the year 1989 to identify the dependentvariables. Publicly-traded firms with a March 31 year-end are selected since thereare twice as many firms that had this year-end than the December 31 year-end.The March 31 year-end also coincides with the Japanese government fiscal year.Unlike the GG study, no size requirement is imposed. The Japanese marketexperienced a crash in 1990 and separate regressions are run for the cross-sec-tional time-series data without the 1990 data in order to evaluate the impact of thecrash.

The sampling frame consists of observations from PACAP files for publiclytraded firms with a March 31 fiscal year-end for which five complete years of dataare available. This provided 6531 observations. From this, firms without any oneof the three measures for IOS are screened leaving a total of 5308 observationsŽ1988, ns1040; 1989, ns1092; 1990, ns1104; 1991, ns1092; 1992, ns

.980 . Table 1 presents the descriptive statistics and correlations among themeasures of IOS. 12 As expected, MKTBKEQ is positively correlated with MKT-

Ž .BKAS and the magnitude of the correlation 0.612 is reasonably high. EP is also,as expected, negatively correlated with MKTBKEQ and MKTBKAS but the

Ž .magnitudes of the negative correlations y0.273 and y0.128, respectively arerelatively low. 13 In order to assess whether the three individual measures are

12 Observations with negative earnings for the EP ratio calculations are excluded.13 Ž .The size of these correlations are similar to the correlations obtained by Gaver and Gaver 1993 .


Table 1Ž .Descriptive statistics for the ratio of market value of assets to the book value of assets MKTBKAS ,

Ž .the ratio of market to book value of equity MKTBKEQ and the EP ratio and the correlations betweenŽ .athe three proxies ns5308

MKTBKAS MKTBKEQ EP

Panel A: DescriptiÕe statisticsMaximum 14.26 244.91 0.434Third quartile 2.35 16.46 0.031Median 1.89 10.9 0.022First quartile 1.55 7.12 0.013Minimum 0.98 0.95 0.000Mean 2.06 13.82 0.024

Panel B: CorrelationsMKTBKAS 1.00

UUUMKTBKEQ 0.612 1.000UUU UUUEP y0.273 y0.128 1.000

UUUp-0.001.

a Ž .n is for the number of observations and it is possible that some firms very few may have less thanŽ .five observations 1988–1992 .

Ž .MKTBKASs AssetsyTotal Common EquityqShares Outstanding=Share Closing Price rAssets.Ž .MKTBKEQs Shares Outstanding=Share Closing Price rTotal Common Equity.

EPsPrimary EPS Before Extraordinary ItemsrShare Closing Price.

common to the measure of IOS employed in this study, common factor analysis isŽ .used Harman, 1976; Gaver and Gaver, 1993 .

Table 2 provides the results of the factor analysis of the 5308 observations.Panel A reports the starting communalities 14 of the individual IOS proxies andPanel B shows the eigenvalues 15 of the reduced correlation matrix. In Panel C,the correlations between the common factor and the three proxies are given. Thesignificant correlations which are in the predicted direction strongly suggest that

Ž .the IOS common factor captures the underlying construct that is common to thethree measures of the IOS. The descriptive statistics of the common factor areprovided in Panel D.

In order to provide a stronger test of the theory, the top and bottom quartile ofŽ .the 5308 observations are selected to represent high growth ns1327 and low

Ž . Ž . Ž . Ž .growth ns1327 firms. Table 3 compares a asset size, b profitability, cŽ . 16regulated vs. unregulated firms, and d keiretsu affiliation distributions for

14 Communalities are the squared multiple correlations obtained by regressing each of the proxieswith the other two proxies.

15 Ž . Ž .Cattrell 1966 and Harman 1976 suggest that if the first eigenvalue exceeds the sum of the threecommunalities, this one common factor explains the intercorrelations among the individual measures.

16 The reason for the lower sample size in Panel D is because the classification for keiretsu isŽ .obtained from Nakatani 1984 who provided information only for manufacturing companies.


Table 2Selected statistics related to common factor analysis of the ratio of market value of assets to the bookvalue of assets, market value to book value of equity and the EP ratio to obtain the IOS factor scoresŽ .ns5308

Panel A: Estimated communality estimatesMKTBKASs0.413 MKTBKEQs0.375 EPs0.077

Panel B: EigenÕaluesMKTBKASs1.086 MKTBKEQs0.0318 EPsy0.254

Panel C: Correlations between common factor and three IOS measuresUUU UUU UUUMKTBKASs0.919 MKTBKEQs0.856 EPsy0.357

( )Panel D: DescriptiÕe statistics of the common factor obserÕationss 5308Maximum 10.131Third quartile 0.277Median y0.150First quartile y0.487Minimum y3.779Mean 0.000

UUUp-0.0001.

Based on these factor scores, growth and non-growth firm were identified as follows: Growth Firms:Ž .Top 25% of the distribution of factor scores ns1327 ; Non-Growth Firms: Bottom 25% of the

Ž .distribution of factor scores ns1327 .Ž .MKTBKASs AssetsyTotal Common EquityqShares Outstanding=Share Closing Price rAssets.Ž .MKTBKEQs Shares Outstanding=Share Closing Price rTotal Common Equity.

EPsPrimary EPS Before Extraordinary ItemsrShare Closing Price.

firms in the sampling frame and the growth and non-growth categories. Aninteresting aspect of Table 3 is that, unlike the GG study there is no predominanceof large firms in the growth sample and, in fact, the large firms are predominantlyin the non-growth sample. A chi-squared test shows that while there are nosignificant differences in the size distribution between each of the growth and

Žnon-growth firms and the sampling frame, there are significant differences p-.0.05, one-tailed between the growth and non-growth firms. Further, both a

Wilcoxon test and a t-test show that there are no differences in profitability 17

Ž . Ž .between the growth 2.545 and the non-growth 2.565 firms. This issue is takenup later in the Section 5. Appendix A reports the industry representation of firmsin the sampling frame and firms in the growth and non-growth firms.

3.2. DescriptiÕe statistics

Table 4 provides descriptive statistics for the dependent variables for bothgrowth and non-growth firms and keiretsu and non-keiretsu firms.

17 Profitability is measured as operating income for year t divided by the market value of the firm atŽ .year-end market values total assets-book value of common equityqmarket value of common equity .


Table 3Ž . ŽDistributions of firms in the total sample ns5308 and firms in the growth top quartile of IOS factor

. Ž .scores and non-growth bottom quartile of IOS factor scores sample

( )Panel A By quartiles of the book Õalue of asset size

Quartiles of book value of assets Total sample Growth firms Non-growth firmsŽ . Ž . Ž . Ž .Y millions ns5308 ns1327 ns1327

Less than 33.3 25% 31.12% 20.42%33.3- A-70.6 25% 24.64% 21.33%70.6- A-205.5 25% 22.48% 24.11%More than 205.5 25% 21.85% 34.14%

( ( ))Panel B By quartiles of profitability operating incomermarket Õalue of firm in the preÕious year

Ž .Quartiles of profitability % Total sample Growth firms Non-growth firmsŽ . Ž . Ž .ns5308 ns1327 ns1327

Less than 1.56 25% 26.78% 25.87%1.56- P -2.37 25% 24.75% 22.54%2.37- P -3.27 25% 21.70% 26.26%More than 3.27 25% 26.78% 25.33%

a( )Panel C By regulated Õs. unregulated firms

Total sample Growth firms Non-growth firmsŽ . Ž . Ž .ns5308 ns1327 ns1327

Regulated 343 130 88Unregulated 4974 1197 1239

(Panel D By keiretsu Õs. non-keiretsu firms. The lower sample size is because these are only( ))manufacturing firms as per Nakatani 1984

Total sample Growth firms Non-growth firmsŽ . Ž . Ž .ns5308 ns1327 ns1327

Keiretsu 836 223 149Non-keiretsu 207 62 30

aRegulated firms are financial, land transport, shipping, air transport, communications and electricityŽ .and gas source: Price Waterhouse, 1992 .

As reported in Panel A of Table 4, growth firms have lower levels of debt intheir capital structure than non-growth firms. The Wilcoxon two-sample test and

Ž .the t-test for differences in means assuming unequal variances show that theŽbook debtrequity ratio and the market debtrequity ratio for growth firms i.e.,

. Ž .mean of 8.416 and 0.363, respectively is significantly p-0.01 lower than forŽ .non-growth firms i.e., mean of 15.958 and 2.195, respectively . These results are

consistent with contracting cost predictions. 18

18 It is worth noting that these test do not control for the role of bank ownership of keiretsu firmsŽ .which is likely to encourage higher levels of debt Nakatani, 1984 .


Table 4Descriptive statistics for book debtrequity ratio, market debtrequity ratio, dividend yield and dividendpayout

( ( ) (Panel A By growth top quartile of IOS factor scores and non-growth bottom quartile of IOS factor) )scores firms

Ž . Ž .Policy variables Growth firms ns1327 Non-growth firms ns1327

Mean First Median Ninth Mean First Median Ninthdecile decile decile decile

Book DebtrEquity Ratio 8.416 2.190 6.050 17.353 15.958 2.894 8.055 30.747Market DebtrEquity Ratio 0.363 0.120 0.307 0.658 2.195 0.509 1.232 4.170

Ž .Dividend Yield % 1.840 0.184 0.530 5.225 1.920 0.451 0.962 2.326Dividend Payout 1.40 0.098 0.317 3.082 1.042 0.136 0.40 1.938

(Panel B By keiretsu Õs. non-keiretsu firms. The lower sample size is because these are only( ))manufacturing firms as per Nakatani 1984

Ž . Ž .Policy variables Keiretsu firms ns836 Non-keiretsu firms ns207

Mean First Median Ninth Mean First Median Ninthdecile decile decile decile

Book DebtrEquity Ratio 7.869 3.585 6.828 12.914 6.855 2.095 5.563 12.240Market DebtrEquity Ratio 0.708 0.263 0.586 1.294 0.622 0.184 0.465 1.192

Ž .Dividend Yield % 1.251 0.337 0.765 1.575 1.561 0.423 0.843 2.427Dividend Payout 1.308 0.167 0.378 1.290 0.942 0.186 0.368 1.441

Book DebtrEquitysTotal LiabilitiesrTotal Common Equity.Ž .Market DebtrEquity RatiosTotal Liabilitiesr Shares Outstanding=Share Closing Price .

Ž .Dividend Yield % sDividends Per SharerPrimary Earnings Per Share Before Extraordinary Items.Dividend PayoutsDividends Per SharerPrice Per Share.

Similarly, there is some evidence that dividend policy is different betweengrowth and non-growth firms. While the t-test did not reveal significant differ-ences in means, the Wilcoxon test shows that the dividend yield ratio is signifi-

Ž . Ž .cantly p-0.001 lower for growth firms mean of 1.840, median of 0.530 thanŽ .for non-growth firms mean of 1.920, median of 0.962 . No significant differences

are found in the payout ratio.Panel B of Table 4 provides descriptive statistics for the policy variables for the

keiretsu vs. non-keiretsu subsample of firms. Both the Wilcoxon two-sample testand t-test for differences in means show that the book debtrequity ratio and

Ž . Žmarket debtrequity ratio are significantly p-0.01 higher for keiretsu i.e.,. Žmean of 7.869 and 0.708 than for non-keiretsu firms i.e., mean of 6.855 and

. Ž .0.622 . These results are consistent with the finding of Nakatani 1984 . There isno difference in payout ratios between keiretsu and non-keiretsu firms but somedifferences are found in the dividend yield ratios. The Wilcoxon two-sample test

Ž .shows that keiretsu firms are significantly p-0.01 associated with lowerdividend yields than non-keiretsu firms. The results using the t-test are similar but

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Table 5Ž . w Ž .Coefficients for policy variables regressed on a growth dummy growdum 0snon-growth firms bottom quartile of IOS factor scores and 1shigh growth

Ž .x Ž .firms top quartile of IOS factor scores , firm size, profitability and dummy variable for regulation 0sunregulated and 1s regulated2Dependent variable n Intercept Growdum Lassets ROM Regul Adj. R F-value

Panel A: Using year-end pricesUUU UUU UUU UUU UUUŽ .DebtrEquity Book 2572 y43.278 y5.692 3.239 y1.173 21.519 0.2158 177.885UUU UUU UUU UUU UUUŽ .DebtrEquity Market 2572 y5.191 y1.605 0.412 y0.193 2.245 0.2869 259.656

Dividend Payout 2571 1.502 0.274 y0.010 y0.113 y0.188 y0.00001 0.981U UUU UUUDividend Yield 2572 y0.012 y0.0002 0.001 0.003 y0.005 0.0196 13.843

Panel B: Using year-end prices excluding 1990 data because of the market crashUUU UUU UUU UUU UUUŽ .DebtrEquity Book 2035 y43.802 y5.482 3.257 y1.102 21.176 0.2103 136.385UUU UUU UUU UUU UUUŽ .DebtrEquity Market 2034 y5.584 y1.671 0.438 y0.186 2.241 0.2836 202.28

Dividend Payout 2034 1.938 0.066 y0.029 y0.124 y0.005 y0.0008 0.574UUU UUUDividend Yield 2034 y0.009 y0.003 0.001 0.003 y0.001 0.021 11.914

Up-0.05.

UUp-0.01.

UUUp-0.001.


Ž .Dividend Yield % sDividends Per SharerPrimary Earnings Per Share Before Extraordinary Items.Dividend PayoutsDividends Per SharerPrice Per Share.GrowdumsDummy Variable, 0sLow Growth, 1sHigh Growth.LassetssLog of Total Assets.ROMsOperating IncomerMarket Value Of The Firm In The Previous Year.RegulsDummy Variable, 0sNon-Regulated, 1sRegulated.

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Table 6Coefficients for policy variables regressed on the investment opportunity set factor scores, firm size, profitability and dummy variable for regulationŽ .0sunregulated and 1s regulated

2Dependent variable N Intercept Factor Lassets ROM Regul Adj. R F-value

Panel A: Using year-end pricesUUU UUU UUU UUU UUUŽ .DebtrEquity Book 5152 y32.607 y1.782 2.397 y0.541 13.842 0.125 185.031UUU UUU UUU UUU UUUŽ .DebtrEquity Market 5152 y4.184 y0.622 0.296 y0.118 1.451 0.194 310.532

U UDividend Payout 5150 1.902 0.195 y0.026 y0.114 y0.098 0.001 2.271UUU UUU U UUUDividend Yield 5152 y0.023 0.001 0.002 0.004 y0.005 0.027 37.311

Panel B: Using year-end prices excluding 1990 data because of the market crashUUU UUU UUU UUU UUUŽ .DebtrEquity Book 4075 y32.27 y1.813 2.381 y0.522 13.416 0.122 142.636UUU UUU UUU UUU UUUŽ .DebtrEquity Market 4075 y4.305 y0.656 0.306 y0.119 1.421 0.192 243.581

UDividend Payout 4073 1.777 0.137 y0.018 y0.129 0.034 0.0006 1.627UUU UUU UUUDividend Yield 4075 y0.021 y0.0006 0.002 0.004 y0.003 0.026 27.841

Up-0.05.

UUp-0.01.

UUUp-0.001.

FactorsComposite Factor Score of MKTBKAS, MKTBKEQ and EP.Book DebtrEquitysTotal LiabilitiesrTotal Common Equity.

Ž .Market DebtrEquity RatiosTotal Liabilitiesr Shares Outstanding=Share Closing Price .Ž .Dividend Yield % sDividends Per SharerPrimary Earnings Per Share Before Extraordinary Items.

Dividend PayoutsDividends Per SharerPrice Per Share.GrowdumsDummy Variable, 0sLow Growth, 1sHigh Growth.LassetssLog of Total Assets.ROMsOperating IncomerMarket Value Of The Firm In The Previous Year.RegulsDummy Variable, 0sNon-Regulated, 1sRegulated.


Ž .marginally significant p-0.10 . The lower dividends for keiretsu firms is alsoŽ . 19consistent with the finding of Nakatani 1984 .

4. Empirical results

The regression analyses 20 are conducted in three stages. The first stage usesthe pooled cross-sectional time-series data and regresses each of the dependent

Ž .variables on the dummy variable growth opportunities Growdum . Firm size,ŽROM and a dummy for industry regulation 0sunregulated industries, and

. 211s regulated industries are used as control variables. Firm size is measured inŽ .terms of the logarithm of total asset Lassets and profitability is defined as in

footnote 12. Table 5 presents the results for the four regression models.The results in Panel A of Table 5 show a significant negative relation between

debt financing and growth opportunities. Firm size is also significantly positivelyrelated to debt financing. As expected, firms that are regulated have higher levels

Ž .of debt Smith and Watts, 1992 . The results for both dividend yield and payoutare insignificant. Similar results are reported in Panel B of Table 5 which excludes1990, thus, suggesting that the 1990 crash had no significant impact on the results.

19 For a discussion of the results, see later part under the Section 5.20 The small discrepancy in the number of observations between Table 3 and the observations in the

Ž .remaining tables is because there were missing values for the control variable profitability ROM .21 Ideally, keiretsu affiliation should have been included as a control variable but the classification by

Ž . Ž .Nakatani 1984 , which is adopted in this study, is only for manufacturing companies Ns317 andinclusion of this variable in the regressions would not only reduce the sample size but also excludefirms in other industries. Additional regressions are conducted later to evaluate the impact of keiretsuaffiliations.

Notes to Table 7:Ž .I s independent variables.Ž .D sdependent variables.U

p-0.05.UU

p-0.01.UUU

p-0.001.FactorsComposite Factor Score of MKTBKAS, MKTBKEQ and EP.Book DebtrEquitysTotal LiabilitiesrTotal Common Equity.



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Table 7Ž . w Ž .Coefficients for one-year ‘lagged’ policy variables regressed on a growth dummy growdum 0snon-growth firms bottom quartile of IOS factor scores and

Ž .x Ž .1shigh growth firms top quartile of IOS factor scores , firm size, profitability and dummy variable for regulation 0sunregulated and 1s regulated forŽ . Ž . Ž . Ž . Ž . Ž . Ž . Ž .the years 1988 I –1989 D , 1989 I –1990 D , 1990 I –1991 D and 1991 I –1992 D

2Dependent variable N Intercept Growdum Lassets ROM Regul Adj. R F-value

( ) ( )Panel A: 1988 I – 1989 DUUU UUU UUU UUU UUUŽ .DebtrEquity Book 483 y42.284 y7.443 3.354 y1.533 17.892 0.225 36.059UUU UUU UU UUU UUUŽ .DebtrEquity Market 483 y6.567 y1.080 0.445 y0.079 1.766 0.312 55.545

Dividend Payout 483 1.680 y0.312 y0.015 y0.021 0.759 y0.0001 0.991UU U UUUDividend Yield 483 y0.027 y0.011 0.003 0.001 y0.006 0.028 4.457

( ) ( )Panel B: 1989 I – 1990 DUUU UUU UUU UUUŽ .DebtrEquity Book 513 y37.32 y2.373 2.977 y2.232 18.109 0.214 35.749

UUU UUU UUU UUU UUU UUUŽ .DebtrEquity Market 513 y3.911 y0.911 0.324 y0.254 1.484 0.299 55.806Dividend Payout 513 y0.275 0.452 0.051 0.126 y0.468 0.0034 1.437

UUU U UUUDividend Yield 513 y0.023 0.0001 0.001 0.008 y0.016 0.058 8.814

( ) ( )Panel C: 1990 I – 1991 DUUU UUU U UUU UUUŽ .DebtrEquity Book 511 y29.902 y5.659 2.470 y1.124 19.607 0.188 30.589

Ž . UUU UUU UUU UUU UUUDebtrEquity Market 511 y3.537 y1.770 0.349 y0.266 2.110 0.282 51.114UU UUU UUUDividend Payout 511 1.095 y0.227 y0.014 y0.096 y0.049 0.029 4.911UUU UU UUU UUUDividend Yield 511 0.006 y0.004 0.0003 y0.00002 y0.003 0.360 72.837

( ) ( )Panel D: 1991 I – 1992 DUUU UUU UUU UUUŽ .DebtrEquity Book 455 y43.033 y6.336 3.088 y0.473 20.165 0.209 31.104UUU UUU U UUU UUUŽ .DebtrEquity Market 455 y7.464 y2.532 0.591 y0.236 3.176 0.286 46.420

UUU UUDividend Payout 455 1.896 y0.199 y0.029 y0.223 y0.281 0.02 3.328UUU UUU UUUDividend Yield 455 0.009 y0.005 0.0002 0.0005 y0.001 0.308 51.39


The second stage of the analysis substitutes the actual factor score for growdumand includes all the observations. The results presented in Table 6 are consistentwith the earlier findings.

To address the potential problem of spurious correlation, because the underly-ing variables are dependent on stock price measured on the same date, the marketdebtrequity and dividend yield were recomputed using the average monthlyclosing stock price for each year excluding the year end price. The result formarket debtrequity is significant in the predicted direction for both the growthdummy variable and the factor scores. No significant result is obtained for thedividend yield. These outcomes are similar to the earlier results using year-endclosing stock prices.

Finally, the results for regressions using ‘lagged’ dependent variables for theyears 1988 to 1992 are reported in Tables 7 and 8. As noted, these results are farmore meaningful given the lag between the identification of growth opportunitiesand the dependent variables.

ŽThe results show that dividend yield becomes significant and in the predicted.direction in three of the four panels in Tables 7 and 8. In particular, the high

adjusted R2 in Panels C and D of Tables 7 and 8 for the dividend yield regressionshould be noted. Similar analysis is carried out using average prices for thefollowing year for the dependent variables market debtrequity ratios and dividendyields. The results are consistent with the findings reported in Tables 7 and 8.Dividend payout is generally insignificant except in Panel C of Table 7 where asignificant result in the right direction is found.

4.1. Additional analysis for keiretsu firms

Further tests are conducted to examine the role of keiretsu vs. non-keiretsufirms in corporate finance and dividend policy. For this purpose, the classification


p-0.05.UU

p-0.01.UUU




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Table 8Coefficients for one-year ‘lagged’ policy variables regressed on the investment opportunity set factor scores, firm size, profitability and dummy variable for

Ž . Ž . Ž . Ž . Ž . Ž . Ž . Ž . Ž .regulation 0sunregulated and 1s regulated for the years 1988 I –1989 D , 1989 I –1990 D , 1990 I –1991 D and 1991 I –1992 D2Dependent variable n Intercept Factor Lassets ROM Regul Adj. R F-value

( ) ( )Panel A: 1988 I – 1989 DUUU UUU UUU UUU UUUŽ .DebtrEquity Book 962 y27.838 y2.868 2.252 y1.216 13.699 0.158 46.134

UUU UUU UUU UUU UUU UUUŽ .DebtrEquity Market 962 y4.319 y0.461 0.285 y0.069 1.281 0.234 74.362Dividend Payout 962 1.674 y0.181 y0.023 y0.005 0.746 0.0011 1.259

U UUUDividend Yield 962 y0.025 y0.004 0.002 0.002 y0.008 0.019 5.664

( ) ( )Panel B: 1989 I – 1990 DUUU UUU UUU UUU UUUŽ .DebtrEquity Book 1026 y25.628 y1.100 2.142 y1.375 13.013 0.134 40.745UUU UUU UUU UUU UUU UUUŽ .DebtrEquity Market 1026 y2.931 y0.443 0.225 y0.138 1.092 0.225 75.516

UU UUDividend Payout 1026 1.021 0.272 y0.037 0.299 y0.313 0.009 3.21U UU UUU UU UUUDividend Yield 1026 y0.047 0.004 0.003 0.008 y0.013 0.081 23.436

( ) ( )Panel C: 1990 I – 1991 DUUU U UUU UUU UUUŽ .DebtrEquity Book 1015 y28.242 y1.181 2.109 y0.342 11.699 0.0972 28.282

Ž . UUU UUU UU UUU UUUDebtrEquity Market 1015 y3.797 y0.651 0.287 y0.120 1.150 0.167 51.863Dividend Payout 1014 2.755 y0.295 y0.090 y0.146 y0.196 y0.003 0.357

U UUU UUU UUU UUUDividend Yield 1015 0.003 y0.002 0.0003 0.00008 y0.003 0.203 65.554

( ) ( )Panel D: 1991 I – 1992 DUU UUU UUUŽ .DebtrEquity Book 922 y33.812 y1.645 2.337 0.179 12.833 0.11 29.557UUU UUU UUUŽ .DebtrEquity Market 922 y6.077 y0.929 0.422 y0.117 2.078 0.181 51.73

UUDividend Payout 922 6.462 y0.209 y0.233 y0.474 y0.420 0.008 2.925UU UUU UU UU UU UUUDividend Yield 922 0.005 y0.002 0.0003 0.0003 y0.001 0.187 53.867

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Table 9Ž . w Ž .Coefficients for policy variables regressed on a growth dummy growdum 0snon-growth firms bottom quartile of IOS factor scores and 1shigh growth

Ž .x Ž .firms top quartile of IOS factor scores , firm size, profitability, dummy variables for regulation 0sunregulated and 1s regulated and keiretsuŽ .0snon-keiretsu and 1skeiretsu

2Dependent variable n Intercept Growdum Lassets ROM Regul Keiretsu Adj. R F-value

Panel A: Using year-end pricesUU UUU UUU UUUŽ .DebtrEquity Book 454 2.211 0.037 0.084 0.594 9.678 2.577 0.0812 9.010

UU UUU U UUU U UUUŽ .DebtrEquity Market 454 0.865 y0.670 0.009 y0.033 0.689 0.103 0.5099 95.254UDividend Payout 454 13.725 y0.457 y0.497 y1.097 y1.716 0.413 0.0025 1.226UUU UUUDividend Yield 454 y0.028 0.0005 0.002 0.004 y0.007 0.001 0.0476 5.533

Panel B: Using year-end prices excluding 1990 data because of market crashUU UU UUU UUUŽ .DebtrEquity Book 356 0.787 0.049 0.161 0.594 8.864 2.506 0.0658 5.997

U UUU U UU U UUUŽ .DebtrEquity Market 356 0.834 y0.706 0.012 y0.036 0.706 0.102 0.5013 72.380Dividend Payout 356 18.031 y0.847 y0.707 y1.255 y2.175 0.969 0.0028 1.198

UUDividend Yield 356 y0.009 y0.002 0.001 0.003 y0.007 0.001 0.0160 2.151

Up-0.05.

UUp-0.01.

UUUp-0.001.

Book DebtrEquitysTotal LiabilitiesrTotal Common Equity.Ž .Market DebtrEquity RatiosTotal Liabilitiesr Shares Outstanding=Share Closing Price

Ž .Dividend Yield % sDividends Per SharerPrimary Earnings Per Share Before Extraordinary Items.Dividend PayoutsDividends Per SharerPrice Per Share.GrowdumsDummy Variable, 0sLow Growth, 1sHigh Growth.LassetssLog of Total Assets.ROMsOperating IncomerMarket Value Of The Firm In The Previous Year.RegulsDummy Variable, 0sNon-Regulated, 1sRegulated.KeiretsusDummy Variable, 0sNon-Keiretsu, 1sKeiretsu.

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Table 10Coefficients for policy variables regressed on the investment opportunity set factor scores, firm size, profitability, dummy variables for regulationŽ . Ž .0sunregulated and 1s regulated and keiretsu 0snon-keiretsu and 1skeiretsu

2Dependent variable n Intercept Factor Lassets ROM Regul Keiretsu Adj. R F-value

Panel A: Using year-end pricesUUU UUU UUU UUUŽ .DebtrEquity Book 1024 1.603 0.312 0.193 0.478 11.796 1.398 0.0954 22.576

UUU UU UU UUU UU UUUŽ .DebtrEquity Market 1024 0.183 y0.392 0.027 y0.031 0.785 0.089 0.3299 101.747UDividend Payout 1024 7.664 0.454 y0.279 y0.583 y0.267 0.209 0.0035 1.719UUU UUUDividend Yield 1024 y0.018 0.001 0.001 0.004 0.005 y0.002 0.0471 11.121

Panel B: Using year-end prices excluding 1990 data because of market crashUUU UUU UUUŽ .DebtrEquity Book 813 0.935 0.262 0.233 0.472 11.187 1.321 0.0886 16.787

UUU UU UUU UUU U UUUŽ .DebtrEquity Market 813 0.151 y0.401 0.031 y0.037 0.765 0.089 0.3272 79.978U UDividend Payout 813 9.602 0.374 y0.379 y0.652 y0.306 0.487 0.0032 1.521

UUU UUUDividend Yield 813 y0.005 y0.002 0.001 0.003 0.005 y0.002 0.0383 7.460

Up-0.05.

UUp-0.01.

UUUp-0.001.


Ž .Dividend Yield % sDividends Per SharerPrimary Earnings Per Share Before Extraordinary Items.Dividend PayoutsDividends Per SharerPrice Per Share.GrowdumsDummy Variable, 0sLow Growth, 1sHigh Growth.LassetssLog of Total Assets.ROMsOperating IncomerMarket Value Of The Firm In The Previous Year.RegulsDummy Variable, 0sNon-Regulated, 1sRegulated.KeiretsusDummy Variable, 0sNon-Keiretsu, 1sKeiretsu.

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Table 11Coefficients for one-year ‘lagged’ policy variables regressed on the investment opportunity set factor scores, firm size, profitability, dummy variables for

Ž . Ž . Ž . Ž . Ž . Ž . Ž .regulation 0sunregulated and 1s regulated and keiretsu 0snon-keiretsu and 1skeiretsu for the years 1988 I –1989 D , 1989 I –1990 D , 1990 I –Ž . Ž . Ž .1991 D and 1991 I –1992 D

2Dependent variable n Intercept Factor Lassets ROM Regul Keiretsu Adj. R F-value

( ) ( )Panel A: 1988 I – 1989 DUUU UUŽ .DebtrEquity Book 204 1.070 y0.096 0.299 y0.095 12.684 1.149 0.0735 4.223

UU UUU UUU UUU UUUŽ .DebtrEquity Market 204 y0.693 y0.218 0.062 0.005 0.790 0.058 0.3575 23.590Dividend Payout 204 5.625 y0.252 y0.234 y0.107 y0.338 0.143 y0.0146 0.415

UUU UUDividend Yield 204 y0.002 0.003 0.0003 0.006 y0.013 y0.004 0.0777 3.337

( ) ( )Panel B: 1989 I – 1990 DUUU U UUUŽ .DebtrEquity Book 208 5.408 0.371 0.036 0.071 14.901 1.598 0.0923 5.210

UUU UUU U UUUŽ .DebtrEquity Market 208 0.616 y0.260 y0.001 y0.028 0.835 0.100 0.3306 21.445UUU UUDividend Payout 208 y3.647 1.112 0.287 y0.131 y0.410 y0.814 0.0645 3.854

UU U UU UUU UUUDividend Yield 208 y0.073 0.007 0.004 0.004 0.001 y0.0001 0.0876 4.976

( ) ( )Panel C: 1990 I – 1991 DUUU U UUUŽ .DebtrEquity Book 203 2.202 0.549 0.142 0.490 13.254 1.768 0.0894 4.964

Ž . UUU UUU U UUUDebtrEquity Market 203 0.716 y0.508 0.001 0.005 1.112 0.157 0.3339 21.254Dividend Payout 203 19.368 y2.097 y0.999 y0.046 y0.749 1.445 y0.0170 0.325

UUU UUU UUUDividend Yield 203 y0.001 y0.003 0.001 0.00001 0.002 y0.001 0.3427 22.067

( ) ( )Panel D: 1991 I – 1992 DU UUU U UUUŽ .DebtrEquity Book 180 0.582 y0.270 0.193 0.703 14.192 1.615 0.1099 5.418

UUU UU UUUŽ .DebtrEquity Market 180 0.014 y0.640 0.039 0.051 1.086 0.148 0.3775 22.711Dividend Payout 180 1.279 y0.325 y0.020 y0.052 y0.434 0.020 0.0013 1.048

UUU UU UUUDividend Yield 180 0.002 y0.003 0.001 y0.00006 0.005 y0.001 0.2586 13.486


Ž .by Nakatani 1984 which is for 317 manufacturing companies is adopted. For theŽperiod 1988–1992, PACAP files carried 836 observations for keiretsu firms 170

.for 1988; 175 for 1989; 171 for 1990; 171 for 1991; 149 for 1992 and 207Žnon-keiretsu firms 43 for each of the years 1988 and 1989; 42 for 1990; 41 for.1991; 38 for 1992 . As in the earlier case, three sets of regressions are run; using

the growdum variable, using the factor scores and using the ‘lagged’ relationships.The results 22 are reported in Tables 9–11. The results, in general, show thatkeiretsu firms have higher debt ratios than non-keiretsu firms. No significantresults are obtained for dividend ratios though the signs for the dividend yield areconsistently negative in Tables 10 and 11. The results for the association betweengrowth opportunities and market debt equity and dividend yield are in generalsimilar to the earlier results. Some of the adjusted R2 are relatively high, thus,suggesting that these models which controlled for the keiretsu variable are morerobust.

5. Discussion and summary

The empirical results support H1 and confirm the association between IOS andŽ .debt financing. Both the dummy variable for growth see Table 5 and the factor

Ž .variable for growth see Table 6 have significant relations with both market andbook debtrequity. The results provide evidence in favor of the contractingargument rather than the signaling argument since in the signaling argument, highgrowth firms issue more debt to signal their funding needs to finance growth

22 The lower number of observations for the various regressions is because of missing values for oneor more of the variables in the regressions. There are inadequate observations for some variables to runthe ‘lagged’ relationships with the growth dummy.


p-0.05.UU

p-0.01.UUU



Dividend PayoutsDividends Per SharerPrice Per Share.GrowdumsDummy Variable, 0sLow Growth, 1sHigh Growth.LassetssLog of Total Assets.ROMsOperating IncomerMarket Value Of The Firm In The Previous Year.RegulsDummy Variable, 0sNon-Regulated, 1sRegulated.KeiretsusDummy Variable, 0sNon-Keiretsu, 1sKeiretsu.


opportunities. 23 It is also worth noting that the results are inconsistent with theŽ .non-debt tax shields NDTS argument which predicts that growth firms which

Ž .have less NDTS e.g., depreciation, depletion and investment tax credits shouldŽ .have more debt Smith and Watts, 1992 .

Firm size is also significantly related to these two ratios. Regulated firms areassociated with higher levels of debt which is consistent with prior studies and theargument that regulation controls incentive problems between shareholders and

Ž .debtholders Smith and Watts, 1992; Gaver and Gaver, 1993 . However, cross-sec-tional time-series data show that the relation between IOS and dividend policyvariables are not significant and in some cases not in the predicted direction. Thisis inconsistent with the results obtained by GG who find a significant relation

Ž .between growth dummy variable and factor scores and dividend yields. Liketheir study, no relation is found between these independent variables and dividendpayout.

However, the relation between IOS, firm size and dividend policies aredifferent when the ‘lagged’ analysis is conducted. In particular, dividend yield isshown to be significantly related to growth opportunities in three of the four 24

panels in each of the Tables 7 and 8, thus, also providing support for H2 and thecontracting argument. This suggests that the use of the ‘lagged’ approach perhapscaptured the relationship more effectively than cross-sectional or cross-sectionaltime-series analysis.

The reason for the lack of significant results for the dividend payout ratiovariable for this and the GG study may be due to an omitted variables problemandror incorrect specification of the model. For example, Agrawal and JayaramanŽ .1994 find that in all equity firms, firms with lower managerial ownership pay

Ž .larger dividends than those with higher ownership. Dempsey and Laber 1992find that, apart from growth rates and ownership, the estimated beta coefficientand the number of common stockholders affect the dividend payout ratio. Theseresults suggest that future studies should re-examine the effects of a wider range ofagency and transaction costs variables on dividend payout ratios.

The finding that growth firms are smaller than non-growth firms overcomes aŽ . Ž .concern raised by Baker 1993 regarding the GG study p. 164 :

The predictions from the theory are perfectly valid and highly intuitive, but arenonetheless based on intuitive and qualitative definitions of what characterizes

23 It is not possible to completely rule out the tax argument since no test was conducted to test thehypothesis because of the lack of data on the tax status of companies.

24 ŽThe loosening up of financial and regulatory restrictions in the late 1980s through to 1990s see.note 10 earlier should not be discounted in considering the strong results for dividend yields in Panels

C and D of Tables 9 and 10.


growth options. This is the reason that a selection criterion that divides firmsinto growth and non-growth samples and ends up with the counter-intuitivefinding that growth firms are larger and more profitable than the non-growthfirms is troubling.

ŽThis study, which shows that non-growth firms are larger but not more.profitable than growth firms, is therefore intuitively more appealing and consis-

tent with predictions. It is also worth noting that large firms are more highlyleveraged which is consistent with the bankruptcy costs evidence obtained by

Ž . Ž .Warner 1977 and Ang et al. 1982 . Similarly, the findings that profitability is inmost cases negatively related to leverage are consistent with findings by Titman

Ž .and Wessels 1988, p. 14 that ‘‘increases in the market value of equity, due to anincrease in operating income, are not completely offset by an increase in the firm’s

Ž .borrowing’’ and the observation of Myers 1984 regarding the ‘pecking ordertheory’ that firms prefer internal to external financing.

The additional keiretsu analysis using a subsample of firms shows that keiretsufirms are associated with higher levels of debt. 25 The results are consistent with

Ž .the finding of Nakatani 1984 who suggests that the higher debt ratios is becauseof the smaller risk of bankruptcy for keiretsu firms since banks are the principalshareholders of these firms. The negative signs for the dividend yield is consistentwith the expectation that keiretsu firms pay lower dividends because intercorporateshareholdings are financed through borrowings and receiving dividends limits the

Žright of the firm to using tax-deductibility of interest payments Nakatani, 1984, p.. 26239 .

This study is subject to a number of caveats. First, as suggested by BakerŽ .1993 , the relation between a firm’s policies and IOS are interdependent and IOScould also be affected by a firm’s debt and dividend policy. In addition, there is aview that a firm’s debt financing has a negative influence on the amount of

Ž .dividends paid Higgins, 1972; McCabe, 1979 . The complexity of this problemand the relation suggest some caution in interpreting the results. Second, any testsof the contracting-cost hypothesis is complicated by the difficulty of measuringIOS. An attempt is made to overcome this difficulty by conducting factor analysison three common proxies and inferring the unobservable IOS from the results. Thehigh and significant correlations between the three measures suggest that the

25 These results should be evaluated in the light of recent evidence which suggest that new rulesgoverning stock issues, increase in foreign ownership and loosening of other restrictions may cause a

Žbreaking down of the differences between keiretsu and non-keiretsu firms Suzuki and Wright, 1985;.Prowse, 1992 .

26 Ž .Nakatani 1984 also suggests that the lower dividends may be explained in terms of the fact thatŽ .keiretsu firms have less incentive to use dividends as a signal. Abegglen 1984, p. 77 notes that for

keiretsu, firms ‘‘especially good profits are not generally recognized in dividend payments but ratherŽ .are recognized in terms of higher payments of bonuses to employees’’. See also Aoki 1987 .


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variables are adequate for this sample. Third, the March 31 fiscal year requirementŽ .means that firms a smaller proportion which had a December 31 fiscal year were

excluded and to this extent could have biased the results. Finally, this study doesnot specifically test the tax hypothesis for corporate finance and dividend policiesand this suggests a possible avenue for future research.

Overall, this study increases our understanding of the relation between IOS andcorporate financial policies and it supplements the evidence of the SW and GGstudies in four ways. First, it provides evidence consistent with contracting theorypredictions in a legal and regulatory environment that is different from that in theUS. Second, it uses cross-sectional time-series data and a ‘lagged’ variableanalysis, which may be more effective in capturing the ‘dynamics’ of the relations.The ‘lagged’ analysis mitigates the problem of spurious correlations and providessome basis for causal inferences. Third, this paper does not exclude small firmsand therefore provides a broader test of the theory. Finally, the finding that there isa higher incidence of larger firms in the non-growth category provides someŽ .albeit indirect evidence that the three measures used in this study adequatelycaptured the IOS.

Acknowledgements

The comments of an anonymous reviewer, the Editor, Ken Lehn, Bikki Jaggi,Raymond Chiang, Larry Lang, Paul Nevell and Judy Tsui are gratefully acknowl-edged.

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Growth opportunities, capital structure and dividend policies in Japan