Capital Structure and Its Product Market Determinants

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Fore School of Management, B 18 Qutab Institutional Area, New Delhi 110016, India

E-mail: [email protected]

Asia-Pacifc Business ReviewVol. VI, No. 2, April - June 2010

pp. 41-49, ISSN: 0973-2470

Capital Structure and Product Market Determinants:

Empirical Evidence from the Indian Automobile Industry

Himanshu Joshi

This paper provides insights into the way in which the capital structure is determined by product market determinants, research and

development activity and protability. This paper is an attempt to test relevance of empirical evidences found in matured markets to

the Indian market condition. Automobile industry is taken up for the study because of its oligopoly nature and easy availability of

product prices. Some of the results are very different from the similar studies conducted in the advanced economies. It is found that

the rms in the same industry can have different capital structures and there is a negative correlation between the protability and

capital structure of the companies. Interestingly, no correlation is found between R&D expenses and capital structure of the company.

It was also concluded that no extra market power is attained because of high leverage.

Keywords: Capital Structure, Product Market, Market Structure, Protability, Market Power, Capital Expenditure

Introduction

Capital structure refers to the way a corporation

nances its assets through some combination of

equity, debt, or hybrid securities. A rms capital

structure is thus, the composition or structure of

its liabilities. The modern theory of capital structure

began with the celebrated paper of Modigliani

and Miller (1958). Their paper paved way for the

development of alternative theories by showingunder what conditions capital structure is irrelevant.

The alternative theories include agency cost theory,

Asymmetric information theory, Product/input market

interactions theory, corporate control considerations

theory and the tax incentive theory. All these theories

have been subjected to extensive empirical testing

in the context of developed countries, particularly

USA. A few studies report international comparison

of capital structure determinants. Similar studies have

been conducted in emerging markets of South East

Asia that provide evidence on capital structure and its

determinants. (Pandey, 2001; Annuar and Shamsher,

1993; Ariff, 1998).

The recent focus of the researches on capital structure

has been on the interaction between capital structure

and product market structure. Brander and Lewis

(1986), Bolton and Scharfstein (1990), Maksimovic

(1988), and Ravid (1988) offer theoretical framework

for linkage between capital structure and market

structure. Phillips (1995) provides surveys of the

theoretical and empirical relationship between capital

structure and market structure. Chevalier (1993), and

Phillips (1995) investigated the empirical relation

between capital structure and market structure for

US Companies. Rathinasamy, Krishnaswamy and

Mantripragada (2000) conducted similar study in the

international context using data from 47 countries.

Predicted cubic relationship between capital structure

and market power and tested it for Malaysia.

Present study is an attempt to nd out the relevance of

capital structure and product market power interaction

evidences in the Indian context. This paper tried to

answer few important questions: Do Firms in the

same industry have same capital structures? Is this

the case that more leverage would lead to aggressive

production and create Market power to the rm?

Do highly leveraged rms tend to indulge in more

research and development activities? Empirical

studies are conducted to nd the relation between

variables like Protability, R&D and sales expenses

with Debt- Equity ratio in case of Indian Automobile

Industry. Auto mobile industry is chosen because of

its oligopoly nature and easy availability of product

prices. Some of the results are very different from the

similar studies conducted in the developed economies.

It is found out that Firms in the same industry can

have different capital structures and there is negative

correlation between the Protability and Debt-Equity

ratio of the companies. Interestingly no correlation is


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Asia-Pacic Business Review Vol. VI, No. 2, April - June 2010

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found in R&D expense with Debt-Equity ratio of the

company.

Theoretical FrameworkFirms raise investment funds in a number of ways.

They can borrow from banks and other nancial

institutions or they can issue various kinds of debt,

preferred stock, warrants, and common equity. A rms

mix of these different sources of capital is referred

to as its capital structure. Capital structure could be

dened in different ways. In the US, it is common to

dene capital structure in terms of long term debt ratio.

In a number of countries, particularly the emerging

markets, companies employ both short term and long

term debt for nancing their assets, including current

assets. For testing the validity of empirical evidencesfound in the developed economies in Indian context

we have dened our dependent variable - capital

structure as long term Debt to Equity ratio.

Market structure implies a rms monopoly, or

oligopoly or competitive power. We have taken up

the case of Indian automobile industry which is

characterised as an oligopoly market. Firms in the

oligopoly market can benet from debt if higher debt

to equity ratios allows them to commit to an aggressive

output policy that they otherwise would not be able

to carry out. (Brander and Lewis, 1986). A rm may

wish to send a message to its competitors that it plansto increase its production. If the competitors ignore

this message, the added production is likely to reduce

the product prices and thus reduce prot for both the

rms and its competitors. However if this message is

credible, the competitors may accommodate the rm

by reducing its output instead of engaging in price war.

In this case, the aggressive policy does increase the

rms prots. When aggregate industry demand for a

product is highly uncertain, higher output generally

increases risk because it leads to higher prots when

product demand turns out to be high, but lower prots

when demand turns out to be low. Hence, since higherleverage increases rms appetite for risk, the greater

a rms leverage, the greater its incentive to produce

at high level of output. So there should be positive

relation between rms capital structure and market

power.

Another important nding in capital structure and

market power interaction is the negative relation

between operating prot and leverage. The relation

reects pecking order of nancing behavior. When

rms generate substantial amounts of cash from their

operations, they tend to pay down debt before payingout dividends and repurchasing shares. When rms

generate insufcient cash to cover investment needs,

they tend to borrow rather than issue stock to cover

the shortfall.

There exists negative relationship between Selling

and Research & Development expenses and capital

structure. Firms with large selling and R&D expenses

may have little taxable earnings and hence, may only

be able to utilize rarely, if at all, debt tax shields. In

addition, rms with high R&D and selling expenses

are likely to be growth rms that produce specialized

products. To the extent that these are indeed growthrms, these rms are not likely to have access to

sizable amounts of debt nancing because of the debt

holder- equity holder conicts.

Literature Review

The modern theory of capital structure began with

the celebrated paper of Modigliani and Miller (1958).

Their paper paved way for the development of

alternative theories by showing under what conditions

capital structure is irrelevant. Harris and Raviv (1991)

have identied ve categories of determinants of

capital structure. Based on the determinants these aresome of the theories.

(i) Agency cost theory

(ii) Asymmetric information theory

(iii) The Theoretical Tax Incentive.

(iv) Corporate control considerations theory

(v) Product/input market interactions theory

A signicant fraction of the effort of researchers has

been devoted to models in which capital structure is

determined by agency costs, i.e., costs due to conictsof interest. Research in this area was initiated by

Jensen and Meckling (1976) building on earlier work

of Fama and Miller (1972). Agency models have been

among the most successful in generating interesting

implications. In particular, these models predict that

leverage is positively associated with rm value,

default probability, extent of regulation, free cash

ow, liquidation value, extent to which the rm is


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Asia-Pacic Institute of Management, New Delhi

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a takeover target, and the importance of managerial

reputation. Also, leverage is expected to be negatively

associated with the extent of growth opportunities,

interest coverage, the cost of investigating rm prospects, and the probability of reorganization

following default. Finally, the result that rm value

and leverage are positively related follows from the

fact that these two endogenous variables move in the

same direction with changes in the exogenous factors.

Therefore, leverage increasing (decreasing) changes

in capital structure caused by a change in one of these

exogenous factors will be accompanied by stock price

increases (decreases).

The introduction into economics of the explicit

modeling of private information has made possible a

number of approaches to explaining capital structure.In these theories, rm managers or insiders are

assumed to possess private information about the

characteristics of the rms return stream or investment

opportunities. This stream of research began with the

work of Ross (1977) and Leland and Pyle (1977).

In another, capital structure is designed to mitigate

inefciencies in the rms investment decisions that

are caused by the information asymmetry. This branch

of the literature starts with Myers and Majluf (1984)

and Myers (1984). Myers and Majluf (1984) imply that

leverage increases with the extent of the informational

asymmetry. Ross (1977), Leland and Pyle (1977),

Blazenko (1987), John (1987), Poitevin (1989), all

derive a positive correlation between leverage and

value in a cross section of otherwise similar rms. Ross

(1977) also predicts a positive correlation between

leverage or value and bankruptcy probability, while

Leland and Pyle (1977) predict a positive correlation

between value and equity ownership of insiders.

Following the growing importance of takeover

activities in the 1980s, the nance literature began to

examine the linkage between the market for corporate

control and capital structure. These papers exploit

the fact that common stock carries voting rightswhile debt does not. Harris and Raviv (1988) and

Stulz (1988), capital structure affects the outcome of

takeover contests through its effect on the distribution

of votes, especially the fraction owned by the manager.

Harris and Raviv (1988) also show that targets of

unsuccessful tender offers will have more debt on

average than targets of proxy ghts. They also show

that among rms involved in proxy ghts, leverage

is lower on average when the incumbent remains in

control.

In theoretical tax incentive, hypothesis is that an

increase in tax rate will increase value of rm tax-shield. The rm reduces income by deducting

paid interest on debt and thereby reducing their tax

liabilities. An increase in tax rates should hence

increase leverage.

Capital structure models based on product/input market

interactions are in their infancy. These theories have

explored the relationship between capital structure

and either product market strategy or characteristics

of products/inputs. The strategic variables considered

are product price and quantity. These strategies are

determined to affect the behavior of rivals, and capital

structure in turn affects the equilibrium strategies

and payoffs. Models involving product or input

characteristics have focused on the effect of capital

structure on the future availability of products, parts

and service, product quality, and the bargaining game

between management and input suppliers.

The models show that oligopolists will tend to have

more debt than monopolists or rms in competitive

industries (Brander and Lewis, 1986), and that the debt

will tend to be long term (Glazer, 1989). If, however,

tacit collusion is important, debt is limited, and debt

capacity increases with the elasticity of demand

(Maksimovic, 1988). Firms that produce products that

are unique or require service and/or parts and rms for

which a reputation for producing high quality products

is important may be expected to have less debt; other

things equal (Titman, 1984). Phillips (1995) provides

surveys of the theoretical and empirical relationship

between capital structure and market structure.

Chevalier (1993), and Phillips (1995) investigated

the empirical relation between capital structure and

market structure for US Companies. Rathinasamy,

Krishnaswamy and Mantripragada (2000) conducted

similar study in the international context using data

from 47 countries. Pandey (2001) predicted cubicrelationship between capital structure and market

power and tested it for Malaysia.

Research Methodology

The data for Indian automobile companies for last six

years have been collected from CMIE Prowess. Capital

structure data for NIFTY fty companies is collected


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from national stock exchange website. Hypotheses

were formulated and statistically tested using various

statistical tools. The tools used in this study are

ANOVA single factor, t-test and correlation. We havetested relationship of capital structure with various

determinants like product market power, research

and development expenditures, Selling expenses and

protability. We have dened our dependent variable

of capital structure as long term debt to equity ratio.

Product market power is dened as average change

in product prices divided by net investment. Product

prices are calculated by dividing annual sales by

number of units being sold. For measuring relationship

between R&D expenditure and capital structure we

have calculated R&D expenses to Sales Ratio. For

measuring relationship between selling expenses and

capital structure we have calculated Sales expenses to

Sales Ratio.

Results and Discussions

Based on theoretical framework we have formulated

the following hypotheses for purpose of empirical

testing:

Hypothesis I: Firms in the same Industry tend to

choose similar capital structure.

Null Hypothesis H0: There is no signicant difference

in capital structure within Indian automobile industryrms.

Alternative Hypothesis H1: There is signicant

difference in capital structure within Indian automobile

industry rms.

Hypothesis II: Firms in different industries would

choose different capital structures.

Null Hypothesis H0: There is no signicant difference

in capital structure for Nifty Fifty rms and Indian

automobile rms.

Alternative Hypothesis H1: There is signicantdifference in capital structure for Nifty Fifty rms and

Indian automobile rms.

Hypothesis III: There is a negative correlation

between proftability and capital structure.

Null Hypothesis H0: There is no correlation between

protability and capital structure for Indian automobile

rms.

Alternative Hypothesis H1: There is a negative

correlation between protability and capital structure

for Indian automobile rms.

Hypothesis IV: There is a negative correlation

between selling expenses and capital structure.


Selling Expense and capital structure for Indian

automobile rms.

Alternative Hypothesis H1: There is a negative

correlation between Selling Expense and capital

structure for Indian automobile rms.

Hypothesis V: There is positive correlationbetween R&D expenses and capital structure.


R&D expenses and capital structure for Indian

automobile rms.

Alternative Hypothesis H1: There is a positive

correlation between R&D Expense and capital


Hypothesis VI: There is a positive correlation

between Market power and capital structure.

Null Hypothesis H0: There is no correlation betweenMarket Power and capital structure for Indian

automobile rms.

Alternative Hypothesis H1: There is a positive

correlation between Market Power and capital


Hypotheses Testing

To test rst hypothesis which is Firms in the same

Industry tend to choose similar capital structure, we

have calculated debt equity ratios for various rms

in Indian automobile industry. Our null hypothesis in

this case therefore is there is no signicant difference

in capital structure within the Indian automobile

industry rms. Table 1 - a shows the data for debt-

equity ratio for various rms in Indian automobile

industry. Firms with Zero or near zero debt are not

included. Table 1 - b shows the statistics of ANOVA

test conducted for debt equity ratios of various rms

in the automobile industry. The P-value (Table 1 - b)


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being less than 0.05 our null hypothesis cannot be

accepted. Therefore rms in the same industry need

not have similar capital structure. The result is against

what has been proved in earlier research conducted

in developed economies. The difference in the result

can be attributed to the difference in the structure of

players in both the countries. In India most of the rmsare either joint venture between domestic and foreign

players or foreign subsidiary. Most of the funding in

these companies is through equity from the holding

companies. Players like Maruti Suzuki, General

Motors and HSCI have Zero tolerance to Debt.

To test our second hypothesis which is, rms in the

different industries would choose different capital

structures, we have compared average debt equity

ratio of Indian automobile industry with average

debt-equity ratio for Nifty 50 companies. Our

null hypothesis in this case therefore is, there is no

signicant difference among the capital structure ofrms from different industries. Table 2 - a shows the

comparative data for average debt-equity ratio for

Nifty fty companies and rms of Indian automobile

industry. Table 2 - b shows the summary statistics of

T-test for debt equity ratio of Indian automobile

rms with Nifty fty companies. The P-value for two

tails is 0.088253142 which is less than 0.05 therefore

rejecting our null hypothesis and proving alternative

hypothesis which is Firms in different industries

would choose different capital structures. The result is

as expected and in line with the other research done in

developed market.

Table 3 shows the Average Debt-Equity Ratio, Average

Protability to Sales Ratio, Average Selling Expense

to Sales Ratio, Average R&D Expense to Sales

Ratio, and Market Power Ratio for Indian Automobile

Firms.

To test our third hypothesis, which is, there is

negative correlation between protability and capital

structure, we have formulated null hypothesis, there

is no correlation between protability and capital

structure for rms in Indian automobile industry and

our alternative hypothesis is that there is negative

correlation between protability and capital structure.

To measure protability we have calculated PBIT to

total assets ratio for Indian automobile industry rms

for last six years (Table 3). Table 4 shows the summary

statistics of correlation coefcient between capital

structure and protability. Since test statistic (-2.6764)

falls out of acceptance level (critical statistics -2.015),

null hypothesis is rejected and alternative hypothesis

is proved to be true. We found that there exists a

negative correlation between protability and capital

structure.

Table 1(a): Debt-Equity Ratios for Various Firms under Indian Automobile Industry

Year 2002 2003 2004 2005 2006 2007 2008

Ford 1.7671 1.588 1.979 2.265 1.174 0.83 HM 1.824 3.609 0.981 1.451 1.318 0.775

Hyundai 0.5409 0.519 0.254 0.273 0.254 0.431

M&M 0.63 0.227 0.441 0.239 0.433 0.471

Mahindra Renault 0 0.438 1.109

Tata Motors 0.457 0.322 0.594 0.414 0.312 0.506

Table 1(b): ANOVA Statistics for Debt Equity Ratios of Various Firms in the Automobile Industry

Source of Variation SS df MS F P-value F Crit.

Between Groups 11.1931 5 2.23861 8.05061 9.42E-05 2.57189

Within Groups 7.50782 27 0.27807

Total 18.7009 32


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To test our fourth hypothesis, which is there is anegative correlation between selling expenses and

capital structure; we have calculated total selling

expense to total sales ratio. Total selling expense

is the summation Selling expenses, advertisement

expenses and distribution expenses. (Table 3). Table 5

shows the summary statistics of correlation coefcient

between the two variables. Our null hypothesis in this

case is that there exist no correlation between selling

expenses and capital structure. Since the test statistic(2.191430043) falls outside the acceptance region

the null hypothesis cannot be true. Ironically in this

case instead of negative correlation one can observe

positive correlation. The reasons for this particular

behavior can be attributed to the reason that all the

products are well tested in various other markets to

be termed special products so they could raise Debt

easily.

Table 2(a): Average Debt-Equity Ratio for Nifty Fifty Companies and Firms of Indian Automobile Industry

2003 2004 2005 2006 2007 2008

Market D-E Ratio 0.74418 0.70846 0.68864 0.7134 0.81218 0.59184Automobile Ind D-E Ratio 0.73101 0.8029 0.57699 0.39339 0.38448 0.41724

Table 2(b): Summary Statistics of T-test for Debt- Equity Ratio of Indian Automobile Firms with Nifty

Fifty Companies

Variable 1 Variable 2

Mean 0.70978 0.551

Variance 0.00521 0.0334

Observations 6 6

Hypothesized Mean Difference 0

df 7

t Stat 1.97945

P(T


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To test our fth hypothesis which is, there is negative

correlation between R&D expenses and capital

structure, we have calculated R&D expense to sales

ratio for rms under study. (Table 3). Table 6 shows the

summary statistics of correlation coefcient between

R&D expense to sales ratio and capital structure for

the Indian automobile rms. Since our test statistics

(-0.226) falls under critical statistics at 5% signicance

level, our null hypothesis is accepted. From the result

it can be inferred that there is no correlation between

R&D expenses and leverage. The reasons for this

particular behavior can be attributed to the technologytransfer from the foreign holding companies to Indian

Companies. Except Tata Motors and Mahindra &

Mahindra, and to some extent Hindustan Motors, no

other company has considerable R& D expenses as

percentage of sales.

To test our last hypothesis which is, there is positive

correlation between Market power and Capital

Structure, we have calculated market power by the

formula (average change in price/ net investment/1000).

(Table 3). Table 7 shows the summary statistics of

correlation between the two variables. Since our Test

statistic (0.682) falls under critical statistics (2.353),

our null hypothesis is not rejected. Thus we found

no correlation between market power and capital for

Indian automobile rms.

Table 4: Summary Correlation between Proftability and Capital Structure.

Average PBIT/Total assets

of Auto Industry

Average D-E ratio of Auto

IndustryAverage PBIT/Total assets of Auto Industry 1

Average D-E ratio of Auto Industry -0.66600459 1

Table 5: Summary Correlation Table between Selling Expenses and Capital Structure

Average of selling exp/sales Debt-Equity Ratio

Average of selling exp/sales 1

Debt-Equity Ratio 0.73863 1

Table 6: Summary Correlation between R&D expenses and capital structure

Average D-E ratio of

Auto Industry

Average R&D to sales

Ratio of Auto Industry

Average D-E ratio of Auto Industry 1

Average R&D to sales Ratio of Auto Industry -0.1118 1

Table 7: Summary Correlation between Market Power and Capital Structure

Average change in price/

capital work in progress

Average debt-equity

ratio

Average change in price/ capital work in progress 1

Average debt-equity ratio -0.490841159 1


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Conclusion

Capital structures of companies in different industries

can be different; the reasons behind this difference can

be attributed to the difference of norms in between

the industries, difference in the products, operational

cycles in the industry and policies of the company.

Firms in the Indian automobile industry have adopted

different capital structures and there is negative

correlation between the Protability and capital

structure of the companies. Some of the results

are very different from the similar studies in the

Developed economies. Interestingly no correlation is

found in R&D expense with Debt-Equity ratio of the

company. Reasons for this behavior can be attributed

to structure of Indian automobile industry, where most

of the companies in the Industry are Indian subsidiaries

of foreign companies and these companies are not

investing sufcient funds in R&D activities. They

normally rely on their foreign holding companies

for technology transfers. This result is also being

conrmed by the fact that Indian companies without

any signicant foreign collaboration (Tata Motors and

Mahindra & Mahindra) show signicant investment

in R&D activity and there seems to be a positive

correlation between their R&D expenses and Capital

Structure. Also percentage marketing expenses as

sales of Automobiles companies in India is less than

their counterparts in Developed economies. We foundno correlation between market power and capital

structure for the rms in Indian automobile industry.

References

Annuar, M. N. and Shamsher, M. (1993), Capital

Structure, Capital Market Review, Vol. 1 (2), pp.

171-177.

Ariff, M (1998), Stock Pricing in Malaysia Corporate

Financial & Investment Management. UPM Press.

Blazenko, George (1987), Managerial Preference,

Asymmetric Information, and Financial Structure,

Journal of Finance, Vol. 42, pp. 839-862.

Bolton, P. and Scharfstein, D. (1990), A Theory

of Production based Agency Problems in Financial

Contracting, American Economic Review, Vol. 80

(1), pp. 59-581.

Brander, J. A. and Lewis, T. R. (1986), Oligopoly and

Financial Structure: The Limited Liability Effect,

American Economic Review, Vol. 76 (5), pp. 956-970.

Chevalier, J. A. (1993), Capital Structure and Product

Market Competition: Empirical Evidence from theSupermarket Industry, American Economic Review,

Vol. 85 (3), pp. 415-435.

Fama, Eugene F. and Merton H. Miller, (1972), The

Theory of Finance, (Holt, Rinehart, and Winston, New

York).

Glazer, Jacob, (1989), Live and Let Live: Collusion

among Oligopolists with Long-Term Debt, Working

Paper, Boston University.

Harris, Milton and Arthur Raviv, (1988), Corporate

Control Contests and Capital Structure, Journal of

Financial Economics, Vol. 20, pp. 55-86.

John, Kose, (1987), Risk-Shifting Incentives and

Signaling through Corporate Capital Structure,

Journal of Finance, Vol. 42, pp. 623-641.

Leland, Hayne and David Pyle, (1977), Information

Asymmetries, Financial Structure, and Financial

Intermediation,Journal of Finance, Vol. 32, pp. 371-

388.

Maksimovic, (1988), Capital Structure in Repeated

Oligopolies,Rand Journal of Economics , Vol. 19, pp.

389-407.

Myers, Stewart C. and Nicholas S. Majluf, (1984),

Corporate Financing and Investment Decisions when

rms have information that Investors do not have,

Journal of Financial Economics, Vol. 13, pp. 187-221.

Pandey, I. M. (2001), Capital Structure and the Firm

Characteristics: Evidence from an Emerging Market,

Working Paper, Indian Institute of Management,

Ahmedabad, India.

Pandey, I. M. (2001), Capital Structure and Market

Power Interaction: Evidence from Malaysia, Working

Paper, Indian Institute of Management, Ahmedabad,

India.

Phillips, G. M. (1995), Increased Debt and Industry

Markets: An Empirical Analysis, Journal of

Financial Economics, Vol. 37 (2), pp. 189-238.

Poitevin, Michael, (1989), Financial Signaling and

the Deep Pocket Argument, Rand Journal of

Economics, Vol. 20, pp. 26-40.


9/9


49

Rathinasamy, R.S., Krishnaswamy, C.R. and

Mantripragada, K.G. (2000), Capital Structure

and Product Market Interaction: An International

Perspective, Global Business and Finance Review,Vol. 5 (2), pp. 51-63.

Ravid, S. Abraham, (1988), On Interactions of

Production and Financial Decisions, Financial

Management, Vol. 8, pp. 87-99.

Ross, Stephen, (1977), The Determination of

Financial Structure: The Incentive Signalling

Approach,Bell Journal of Economics, Vol. 8, pp. 23-

40.

Stulz, Rene, (1988), Managerial Control of Voting

Rights: Financing Policies and the Market for

Corporate Control,Journal of Financial Economics,

Vol. 20, pp. 25-54.Titman, Sheridan (1984), The Effect of Capital

Structure on Firms Liquidation Decision,Journal of

Financial Economics, Vol. 13, pp. 137-151.

Capital Structure and Its Product Market Determinants

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