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Asia-Pacific Business Review
Vol. 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 profitability. 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 firms in the same industry can have different capital structures and there is a negative correlation between the profitability 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, Profitability, Market Power, Capital Expenditure

Introduction
Capital structure refers to the way a corporation finances its assets through some combination of equity, debt, or hybrid securities. A firm’s 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 showing under 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 find 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 firm? Do highly leveraged firms tend to indulge in more research and development activities? Empirical studies are conducted to find the relation between variables like Profitability, 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 Profitability and Debt-Equity ratio of the companies. Interestingly no correlation is

Fore School of Management, B – 18 Qutab Institutional Area, New Delhi – 110016, India E-mail: himjoshin@rediffmail.com

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

Theoretical Framework
Firms raise investment funds in a number of ways. They can borrow from banks and other financial institutions or they can issue various kinds of debt, preferred stock, warrants, and common equity. A firm’s mix of these different sources of capital is referred to as its capital structure. Capital structure could be defined in different ways. In the US, it is common to define 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 financing their assets, including current assets. For testing the validity of empirical evidences found in the developed economies in Indian context we have defined our dependent variable - capital structure as long term Debt to Equity ratio. Market structure implies a firm’s 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 benefit 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 firm may wish to send a message to its competitors that it plans to increase its production. If the competitors ignore this message, the added production is likely to reduce the product prices and thus reduce profit for both the firms and its competitors. However if this message is credible, the competitors may accommodate the firm by reducing its output instead of engaging in price war. In this case, the aggressive policy does increase the firm’s profits. When aggregate industry demand for a product is highly uncertain, higher output generally increases risk because it leads to higher profits when product demand turns out to be high, but lower profits when demand turns out to be low. Hence, since higher leverage increases firm’s appetite for risk, the greater a firm’s leverage, the greater its incentive to produce at high level of output. So there should be positive relation between firm’s capital structure and market power. Another important finding in capital structure and market power interaction is the negative relation

between operating profit and leverage. The relation reflects pecking order of financing behavior. When firms generate substantial amounts of cash from their operations, they tend to pay down debt before paying out dividends and repurchasing shares. When firms generate insufficient 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, firms with high R&D and selling expenses are likely to be growth firms that produce specialized products. To the extent that these are indeed growth firms, these firms are not likely to have access to sizable amounts of debt financing because of the debt holder- equity holder conflicts.

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 identified five categories of determinants of capital structure. Based on the determinants these are some 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 significant 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 conflicts of 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 firm value, default probability, extent of regulation, free cash flow, liquidation value, extent to which the firm is

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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 firm prospects, and the probability of reorganization following default. Finally, the result that firm 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, firm managers or insiders are assumed to possess private information about the characteristics of the firm’s 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 inefficiencies in the firm’s 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 firms. 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 1980’s, the finance 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 rights while 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 fights. They also show that among firms involved in proxy fights, 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 firm taxshield. The firm 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 firms 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 firms 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 cubic relationship 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 fifty 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 have tested relationship of capital structure with various determinants like product market power, research and development expenditures, Selling expenses and profitability. We have defined our dependent variable of capital structure as long term debt to equity ratio. Product market power is defined 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.

firms. Alternative Hypothesis H1: There is a negative correlation between profitability and capital structure for Indian automobile firms. Hypothesis IV: There is a negative correlation between selling expenses and capital structure. Null Hypothesis H0: There is no correlation between Selling Expense and capital structure for Indian automobile firms. Alternative Hypothesis H1: There is a negative correlation between Selling Expense and capital structure for Indian automobile firms. Hypothesis V: There is positive correlation between R&D expenses and capital structure. Null Hypothesis H0: There is no correlation between R&D expenses and capital structure for Indian automobile firms. Alternative Hypothesis H1: There is a positive correlation between R&D Expense and capital structure for Indian automobile firms. Hypothesis VI: There is a positive correlation between Market power and capital structure. Null Hypothesis H0: There is no correlation between Market Power and capital structure for Indian automobile firms. Alternative Hypothesis H1: There is a positive correlation between Market Power and capital structure for Indian automobile firms.

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 significant difference in capital structure within Indian automobile industry firms. Alternative Hypothesis H1: There is significant difference in capital structure within Indian automobile industry firms. Hypothesis II: Firms in different industries would choose different capital structures. Null Hypothesis H0: There is no significant difference in capital structure for Nifty Fifty firms and Indian automobile firms. Alternative Hypothesis H1: There is significant difference in capital structure for Nifty Fifty firms and Indian automobile firms. Hypothesis III: There is a negative correlation between profitability and capital structure. Null Hypothesis H0: There is no correlation between profitability and capital structure for Indian automobile

Hypotheses Testing
To test first hypothesis which is Firms in the same Industry tend to choose similar capital structure, we have calculated debt equity ratios for various firms in Indian automobile industry. Our null hypothesis in this case therefore is “there is no significant difference in capital structure within the Indian automobile industry firms”. Table 1 - a shows the data for debtequity ratio for various firms 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 firms in the automobile industry. The P-value (Table 1 - b)

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Table 1(a): Debt-Equity Ratios for Various Firms under Indian Automobile Industry Year Ford HM Hyundai M&M Mahindra Renault Tata Motors 0.457 0.322 0.594 0.5409 2002 1.7671 2003 1.588 1.824 0.519 0.63 2004 1.979 3.609 0.254 0.227 2005 2.265 0.981 0.273 0.441 2006 1.174 1.451 0.254 0.239 0 0.414 2007 0.83 1.318 0.431 0.433 0.438 0.312 0.471 1.109 0.506 0.775 2008

Table 1(b): ANOVA Statistics for Debt –Equity Ratios of Various Firms in the Automobile Industry Source of Variation Between Groups Within Groups Total SS 11.1931 7.50782 18.7009 df 5 27 32 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 Profitability 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 profitability and capital structure, we have formulated null hypothesis, there is no correlation between profitability and capital structure for firms in Indian automobile industry and our alternative hypothesis is that there is negative correlation between profitability and capital structure. To measure profitability we have calculated PBIT to total assets ratio for Indian automobile industry firms for last six years (Table 3). Table 4 shows the summary statistics of correlation coefficient between capital structure and profitability. 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 profitability and capital structure. MS 2.23861 0.27807 F 8.05061 P-value 9.42E-05 F Crit. 2.57189

being less than 0.05 our null hypothesis cannot be accepted. Therefore firms 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 firms are 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, firms 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 significant difference among the capital structure of firms from different industries. Table 2 - a shows the comparative data for average debt-equity ratio for Nifty fifty companies and firms of Indian automobile industry. Table 2 - b shows the summary statistics of T-test for debt –equity ratio of Indian –automobile firms with Nifty fifty companies. The P-value for two tails is 0.088253142 which is less than 0.05 therefore rejecting our null hypothesis and proving alternative

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Table 2(a): Average Debt-Equity Ratio for Nifty Fifty Companies and Firms of Indian Automobile Industry 2003 Market D-E Ratio Automobile Ind D-E Ratio 0.74418 0.73101 2004 0.70846 0.8029 2005 0.68864 0.57699 2006 0.7134 0.39339 2007 0.81218 0.38448 2008 0.59184 0.41724

Table 2(b): Summary Statistics of T-test for Debt- Equity Ratio of Indian – Automobile Firms with Nifty Fifty Companies Variable 1 Mean Variance Observations Hypothesized Mean Difference df t Stat P(T