Determinants of Capital Structure of Firms in the Manufacturing Sector of Firms. in Indonesia. Dissertation. To obtain the degree of

Transcription

1 Determinants of Capital Structure of Firms in the Manufacturing Sector of Firms in Indonesia Dissertation To obtain the degree of Doctor of Business Administration at the Maastricht School of Management, under authority of the Dean Director Prof. dr. Peter P. de Gijsel to be defended in public on May, 2012 by Siti Rahmi Utami born in Jakarta (Indonesia) 1

2 Published by: Maastricht School of Management P.O. Box BE Maastricht The Netherlands Siti Rahmi Utami, Determinants of Capital Structure of Firms in the Manufacturing Sector of Firms in Indonesia. DBA Dissertation, Maastricht School of Management, Maastricht With references. With summary in English. Key words: Capital Structure/Pecking Order Theory/Trade-off Theory/Firm Life Cycle/Signalling Theory/Asymmetric Information/Agency Cost Theory ISBN: Cover: Stoerebinken, The Netherlands Printing: Gildeprint, The Netherlands 2012 by Siti Rahmi Utami, Maastricht School of Management. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without prior written permission of the publisher. 2

3 This dissertation is approved of by the Doctoral Supervisor: Prof. Eno L. Inanga Maastricht School of Management, The Netherlands Composition of the Evaluation Committee: Prof. Dr. Ir. E. J. de Bruijn Twente University, The Netherlands Prof. Dr. Geert Braam RA 3

4 ACKNOWLEDGEMENTS It is with a lot of gratitude and appreciation that I acknowledge the help of my supervisor, Professor Eno L. Inanga, who has helped me to complete this Draft DBA thesis. The Draft DBA thesis would not have reached this stage in the present form without his help. He has given me support throughout the entire process. I am hugely indebted to him for all the hours he spent reading my texts, writing suggestions and comments for me, and helping me to shape my thinking in many ways. I greatly appreciate his expertise in the field of my research. Likewise, I would also like to express my gratefulness to Professor Dadan, from Trisakti University, Indonesia, for his encouragement and guidance. I also owe many thanks to the administrative support I enjoyed from the Doctoral Office at MSM, as well as the administration office at TIBS, Indonesia, are worthy of a mention with special thanks. I must express my profound thanks to my parents (especially my father, Professor Gani SH), without their support, I would not have achieved this stage. Last, but not least, I would also like to thank to my friends, I have learned many things from them. 4

5 TABLE OF CONTENTS ACKNOWLEDGEMENTS... 4 EXECUTIVE SUMMARY INTRODUCTION Background of the Research The Importance of Capital Structure Theory Research Motivation Problem Identification Research Questions Major Research Questions Minor Research Questions Research Objectives Scope and Limitation of the Study Expected Contribution Organisation of the Study AN OVERVIEW OF THE CAPITAL STRUCTURE OF INDONESIAN MANUFACTURING FIRMS Indonesian Capital Market History of Indonesia Stock Exchange Stock Price Index in the Indonesian Capital Market Description of the LQ45 Index Characteristics of the Research Sample Leverage Analysis LITERATURE REVIEW Theories of Capital Structure Modigliani-Miller Theory The Capital Structure Theory The Conclusions What Variables We Use for Our Research, and Why These, Theories Predictions of the Relationship between Variables, and Some Previous Research Findings Selected Variables regarding Capital Structure for Research Question 1a, 1b, 1c, 1d, and 1e 40 5

6 3.2.2 Selected Variables for Research Question Selected Variables for Research Question 3a, 3b, and 3c Selected Variables for Research Question CONCEPTUAL FRAMEWORK Conceptual Framework for Research Question 1a, 1b, 1c, 1d, and 1e Previous Research regarding Capital Structure Determinants Conceptual Framework for Research Question Conceptual Framework for Research Question Conceptual Framework for Research Question RESEARCH METHODOLOGY Research Design Research Strategy Quantitative Strategy Mixed Method Strategy Data Collection Sampling Design and Procedure Variables Measurement Variable of Hypothesis Measuring Variables of Hypotheses 2, 3, and Hypotheses Testing Hypothesis Hypothesis Hypothesis Hypothesis Regression Analysis A. The Un-standardised Beta Coefficients B. The Standardised Beta Coefficients C. Analysis of Variance (ANOVA) D. The Coefficient of Determination (R 2 ) E. Descriptive Statistics F. Regression Assumptions of Hypothesis The Credibility of Research Findings

7 5.8.1 Reliability Validity Generalisability The Limitations of Research Design PRESENTATION OF DATA AND ANALYSIS OF RESULTS Research Question 1, Hypotheses, Hypotheses Testing, and Result Analysis Research Question Hypothesis One (H1) Testing the Hypothesis Analysis of Results Research Question 2, Hypothesis 2, Hypothesis Testing, and Result Analysis Research Question Hypothesis Testing the Hypothesis Analysis of Quantitative Results of Hypothesis Qualitative Analysis of Hypothesis Research Question 3, Hypothesis, Hypothesis Testing, and Result Analysis Research Question Three Hypothesis Testing the Hypothesis Analysis of Results Research Question 4, Hypothesis, Hypothesis Testing, and Result Analysis Research Question Hypothesis Testing Hypothesis Sample Description Analysis of Results Capital Structure over Firm s Life Cycle Frequency Statistical Power Analysis of Hypotheses 1, 2, 3, and Regression Assumptions of Hypotheses 1, 2, 3, and Multicollinearity Autocorrelation

8 3. Heteroscedasticity Normally Distributed Results of Panel Data Regression Analysis and the Comparison to Regression Analysis CONCLUSION Conclusion Conclusion regarding Result and Its Consistency with Condition of Indonesian Capital Market To What Extent is the Study Scientifically Relevance Recommendations and Suggestions for Further Research Suggestions for Managers Managerial Implication BIBLIOGRAPHY APPENDIX APPENDIX A APPENDIX B APPENDIX C APPENDIX D APPENDIX E

9 EXECUTIVE SUMMARY The objectives of this research are: to investigate the determinants of capital structure of the firms in the manufacturing sector in Indonesian capital market; to analyse how firms in the manufacturing sector raise capital for investments, internally or externally (with debt, equity, or debt to repurchase equity); to examine if debt policy does matter; what will happen to the firm s stock price if firms issue new debt, issue new equity, or issue debt to repurchase equity; and to examine within the context of a firm s life cycle whether we can expect that growth-small firms follow the pecking order more closely than mature-large firms. Therefore, we examine 4 major hypotheses. By using regression analysis we test all hypotheses, while for hypothesis 2 we use qualitative analysis, too, and for hypotheses 2 and 4 we also apply an augmented model. Overall, our results showed that under the linear regression model, firms exhibit as follows. For hypothesis 1, profitability has a negative significant regression coefficient on shortterm leverage; long-term leverage; total leverage, and on market leverage. Tangibility has a negative significant regression coefficient on short-term leverage, while tangibility has a positive significant regression coefficient on long-term and market leverage. Tangibility also has a positive but not significant regression coefficient on total leverage. Size, has a positive, yet not significant regression coefficient on short-term leverage and total leverage, while size has a negative, yet not significant regression coefficient on long-term leverage, and size has a negative significant regression coefficient on market leverage. Risk has a positive significant regression coefficienton short-term leverage and total leverage while risk has a negative significant regression coefficient on long-term leverage. Risk also has a positive but not significant regression coefficient on market leverage. Growth has a positive significant regression coefficient on short-term, long-term, and total leverage; however, growth has a negative significant regression coefficient on market leverage. For hypothesis 2, we can conclude that the financing deficit has positive significant effects on the net debt issue and on net equity issue. This result suggests that high deficit firms would tend to issue more net debt and net equity to finance their financing deficit. The financing deficit has negative, yet not significant effects on newly retained earning. This result suggests that high deficit firms would not tend to use newly retained earning to finance the financing deficit. The financing deficit has negative, but not significant effects on repurchase equity. This result suggests that high deficit firms would not tend to repurchase equity to finance the financing deficit. From the descriptive table, we see that the amount of net debt issue is more than net equity issue and it is consistent with regression results. For the augmented model, our result shows a positive coefficient on the financial deficit and also on the squared deficit term. However, for the squared deficit term, the coefficient was not significant. Therefore, we conclude that our firm sample firm prefers external to internal financing and debt to equity if external financing is used. For hypothesis 3, the results indicate that net debt has no positive significant impact on the stock price of from January to December and on the yearly stock price. Net equity has no negative significant impact on the stock price from January to December and on the yearly stock price. This result suggests that firms that issue more net equity would tend to have decreasing 9

10 stock price, while issuing more net debt, the firm would tend to have increasing stock price. The result also suggests that firms repurchasing equity would tend to have increasing monthly and yearly stock price. For hypothesis 4, the growth firms, we conclude that the financing deficit has positive significant effects on the net debt issue and on the net equity issue, and financing deficit has negative significant effects on newly retained earning. For mature firms, we conclude that the financing deficit has positive significant effects on the net debt issue and the net equity issue, while a financing deficit has negative insignificant effects on newly retained earning. From these results, we conclude that our mature and growth firm prefers external to internal financing and debt to equity if external financing is used. Overall, we find that the pecking order theory describes the financing patterns of growth firms better than mature firms. 10

11 1. INTRODUCTION 1.1 Background of the Research The Importance of Capital Structure Theory At the time a firm faces a financial deficit that affects its financial condition, the manager of the firm should be able to make a managerial decision as well as a financial decision in order to maintain the viability of the firm. One way that can be chosen is to undertake a capital restructuring, especially debt restructuring. The decision taken on debt restructuring, of course, requires expertise and analystic capabilities so managers can make the right decisions of financial restructuring for the company. An ideal composition of capital structure which consists of debt and equity, will minimise the cost of capital and maximise the firm s value. Therefore, it is important for the firm s manager to understand the theory of capital structure. The sources of funds include retained earnings, debt, and equity. Retained earning is the cheapest fund for the funding source as it does not have explicit costs in the same way as funds obtained from outside sources. When the company uses debt to finance investments which has an impact on costs rising in its capital structure, the company will have a financial risk, because the company must consider their priority in the structure of debt, debt maturity, decision of mixed debt to certain parties or to the investor, and other types of debt contracts (Peirson, Brown, Easton and Howard, 2002; Barclay et al., 2003). If a firm uses stocks as its capital structure, either common stocks or preferred stocks, then the shareholders of those stocks are the owner of the company. While debt has due date, the stocks do not have one. Thus the repayment of stocks is not necessarily required since stocks are liquidated if the company went bankrupt. Issuing the stocks may reduce the authority of the old owners in the company. To maintain the dominance of the existing owner of the company, the issuance of stocks is managed not to cross the line of power. The cost of the issuance of stocks is dividend which will be distributed to shareholders. Furthermore, debt can be treated as taxdeductible expenses, but common stock dividend payments and preferred stocks are not taxdeductible. Firm s capital structure decision can be viewed from the following theories: Modigliani- Miller theory, pecking order theory, and trade-off theory. The theory of business finance in a modern sense starts with the Modigliani and Miller (1958) capital structure irrelevance proposition. Before them, there was no generally established theory of capital structure. The debate about how and why firms choose their capital structure began in 1958 (Myers, 2001), when Modigliani and Miller (1958) published their famous arbitrage argument showing that the market value of any firm is independent of its capital structure. Modigliani and Miller start their theory by assuming that the firm has a particular set of expected cash flows. When the firm chooses a certain proportion of debt and equity to finance its assets, what it has to do is to divide up the cash flows among investors. Investors and firms are assumed to have equal access to financial markets, which allows for homemade leverage. As a result, the leverage of the firm has no effect on the market value of the firm. Modigliani and Miller s theory influenced the early development of other capital structure theory. 11

12 The introduction of taxation effects implies that firms should, theoretically, try to increase their debt levels as much as possible (Miller, 1988). However, other theorists (for example Stiglitz, 1974; 1988) added limitations to the optimal level of firm debt by arguing that bankruptcy costs enhance as the firm s level of debt increases, and this places a higher limit on the amount of debt that should be present in a firm s capital structure. This evolved into the static trade-off theory, which proposes that firms attempt to achieve an optimal capital structure that maximises the value of the firm by balancing the tax benefits, with the bankruptcy costs, associated with increasing levels of debt (Myers, 1984). Some researchers have identified problem areas in the capability of the static trade-off theory to explain actual firm behaviour. For example Myers (2001) argued that the static trade-off theory implies that highly profitable firms should have high debt ratios in order to shield their large profits from taxation, whereas in reality, highly profitable firms tend to have less debt than less profitable firms. Warner (1977) suggested that bankruptcy costs are much lower than the tax advantages of debt, implying much higher debt levels than predicted by the theory. There is, however, also some empirical evidence and theoretical support for the idea that firms, at least in part, raise their capital structure to take advantage of the interest tax shield (net of the interest tax burden to investors), while ensuring that they avoid acquiring excessively high financial distress costs. For example, Kayhan and Titman (2004) found that, over the long term, firms do tend to move towards target debt ratios consistent with the theory. Static trade-off theory therefore offers one possible explanation of how firms choose their capital structure. Myers observed how firms actually structure their balance sheets, and found that firms tend to follow a pecking order in financing their projects: first they use internal equity, then debt, and only then do they use external equity (Myers, 1984). In contrast to Ross (1977), who argued that firms use more debt to overcome information asymmetries and signal better prospects, Myers (2001) used information asymmetries to argue that managers are unlikely to issue equity, because they fear it will signal that the stock price is overvalued. In addition to the evidence presented by Myers, several other studies have given support to the pecking order theory. For instance, Allen (1993), like Fama and French (1988), found that leverage is inversely related to profitability, which supports the pecking order theory view that debt is only issued when there is insufficient retained income to finance investment. Therefore, capital structure decision is influenced by a pecking order preference, which has advantages and disadvantages based on the pecking order theory, and trading off cost and benefit of using debt based on trade-off theory, in order to maximise return and minimise cost of capital. Besides capital structure, the decision is influenced by the pecking order preference and the trading off cost and benefit of using debt, capital structure decision is influenced by the firm s life cycle where the firm exist and may consider the firm s characteristics. Capital structure life stage theory is conspicuously underdeveloped. Although mentioned in text-books (Damodaran, 2001) and obliquely in some research (for example Morgan and Abetti, 2004), and even referred to in the development of some of the other major theories (for example Myers, 2001), the idea that the capital structure of a firm may be related to its life stage, appears to have received very little direct theoretical or empirical examination. Some of the organisational life stage theory research has suggested that changing life stages may require changes in the way the firm is financed. Thus the firm s financing characteristics change from one life stage to the next stage. 12

13 The pecking order theory describes the financing patterns of growth firms better than of mature firms as mature firms are more closely followed by analysts and are better known to investors, and hence should suffer less from problems of information asymmetry. Our result is consistent with the theory, and also consistent with the previous research findings of Shyam- Sunder and Myers (1999). They propose a direct test of the pecking order and find strong support for the theory among a sample of large firms. Older and more mature firms are more closely followed by analysts and are better known to investors, and hence, should suffer less from problems of information asymmetry. For example, a good reputation (such as a long credit history) mitigates the adverse selection problem between borrowers and lenders. Thus, mature firms are able to obtain better loan rates compared to their younger firm counterparts (Diamond, 1989). The theory s prediction that firms with the greatest information asymmetry problems (specifically young growth firms) are exactly those which should be raising financing choices according to the pecking order theory. In general, the significant difference between mature and young firms is not that mature firms are larger, but because they are more mature which implies that mature firms are older, more stable, higher profitable with few growth opportunities and good credit histories. Growth firms are thus more suited to use internal funds first, and then debt before equity for their financing needs. As mentioned above, capital structure decision is also affected by a firm s characteristics. These characteristics are potentially contentious (Titman and Wessels 1988). Each theory of capital structure gives the different implication on how the firm s characteristics influence the firm s capital structure choices. In order to identify which of the firm s characteristics that have significant effect on capital structure based on theories in the context of Indonesian firms, so this research concentrates on a group of variables identified in the previous literature. The selected explanatory variables are firm size, risk, profitability, tangibility and growth opportunities. For profitability, the pecking order theory, based on works by Myers and Majluf (1984) suggests that firms prefer internal funds rather than external funds. If external finance is required, the first choice is to issue debt, hybrid, then eventually equity as a last resort (Brealey and Myers, 1991). This behaviour may be due to the costs of issuing new equity, as a result of asymmetric information or transaction costs. All things being equal, the more profitable the firms are, the more internal financing they will have, and therefore we should expect a negative relationship between leverage and profitability. However, from the trade-off theory point of view more profitable firms are exposed to lower risks of bankruptcy and have greater incentive to employ debt to exploit interest tax shields. For tangibility, according to the pecking order theory and the trade-off theory, a firm with a large amount of fixed asset can borrow at a relatively lower rate of interest by providing the security of these assets to the creditors. Having the incentive of getting debt at a lower interest rate, a firm with a higher percentage of fixed asset is expected to borrow more as compared to a firm whose cost of borrowing is higher because of having less fixed assets. Thus, we expect a positive relationship between tangibility of assets and leverage. From a pecking order theory perspective, firms with few tangible assets are more sensitive to informational asymmetries. These firms will thus issue debt rather than equity when they need external financing (Harris and Raviv, 1991), leading to an expected negative relation between the importance of intangible assets and leverage. 13

14 For size,, according to trade-off theory, first, large firms don t consider the direct bankruptcy costs as an active variable in deciding the level of leverage as these costs are fixed by constitution and constitute a smaller proportion of the total firm s value. And also, larger firms being more diversified have lesser chances of bankruptcy (Titman and Wessels 1988). Following this, one may expect a positive relationship between size and leverage of a firm. According to pecking order theory, Rajan and Zingales (1995) argue that there is less asymmetrical information about the larger firms. This reduces the chances of undervaluation of the new equity issue and, thus, encourages the large firms to use equity financing. This means that there is a negative relationship between size and leverage of a firm. For risk, according to these theories, the pecking order theory and trade-off theory, we can expect that firms with higher income variability have lower leverage (Bradley et al., 1984; Kester, 1986; Titman and Wessels, 1988), since higher variability in earnings indicates that the probability of bankruptcy increases. Firms that have a high operating risk can lower the volatility of the net profit by reducing the level of debt. A negative relation between the operating risk and the leverage is also expected from a pecking order theory perspective: firms with a high volatility of results try to accumulate cash during good years, to avoid under-investment issues in the future. For growth, by applying pecking order arguments, growing firms place a greater demand on the internally generated funds of the firm. Consequentially, firms with a relatively high growth will tend to issue securities less subject to information asymmetries, i.e. short-term debt. This should lead to firms with relatively higher growth having more leverage. Following trade-off theory, for companies with growth opportunities, the use of debt is limited as in the case of bankruptcy, the value of growth opportunities will be close to zero, growth opportunities are particular cases of intangible assets (Myers, 1984; Williamson, 1988 and Harris and Raviv, 1990). Firms with less growth prospects should use debt because it has a disciplinary role (Jensen, 1986; Stulz, 1990). Firms with growth opportunities may invest suboptimally, and therefore creditors will be more reluctant to lend for long horizons. This problem can be solved by short-term financing (Titman and Wessels, 1988) or by convertible bonds (Jensen and Meckling, 1976; Smith and Warner, 1979). Furthermore, while the literature is rich in studies that examine the importance of firmspecific factors in determining a firm s financing choice, empirical evidence on the effect of capital structure choice on stock market reaction is limited. When a firm issues, repurchases or exchanges one security for another, it changes its capital structure. What are the valuation effects of these changes? There are several theories which explain the relationship between capital structure and stock price. Based on signalling through capital structure, as the increased level of leverage is accompanied by a higher risk of bankruptcy, the increased level of debt indicates the confidence of the management in the future prospects of the firm. Hence, it carries greater conviction than a mere announcement of undervaluation of the firm by the management. On the other hand, an issue of equity is a signal that the firm is overvalued. The market concludes that the management has decided to offer equity because it is valued higher than its intrinsic worth by the market. The markets normally react favourably to moderate increases in leverage and negatively to a fresh issue of equity. Under the trade-off theory, firms will only take actions if they expect profits. An implication of the theory is that the market reaction to both equity and debt securities will be positive. The market response to a leverage change consists of two pieces of information: the revelation of the information that the firm s conditions have changed, necessitating financing, and the impact of the financing on security valuations. The information contained in security issuance 14

15 decisions could be either bad news or good news. It might be bad news if the company is issuing securities, because the company actually needs more resources than anticipated to carry out operations. It would be good news if the company is issuing securities to take advantage of a promising new opportunity that was not previously anticipated. A company may also issues securities to anticipate a change in future needs. This indicates that the trade-off theory by itself places no apparent limitations on the effect of market valuation of issuing decisions. Jung et al. (1996) suggest an agency perspective and argue that equity issues by firms with poor growth prospects reflect agency problems between managers and shareholders. If this is the case, then stock prices would react negatively to news of equity issues. The pecking order theory is usually interpreted as predicting that securities with more adverse selection (equity) will result in more negative market reaction. Securities with less adverse selection (debt) will result in less negative or no market reaction. This does of course, still rest on some assumptions about market anticipations. Literature offers various explanations for buybacks. One of these explanations has theoretical backgrounds and some are formed from empirical studies. The undervaluation hypothesis is explaining our hypotheses. Stock repurchases offer flexibility in the choice to distribute excess funds and when to distribute these funds. This flexibility in timing is valuable because firms can wait to repurchase until the stock price is undervalued. The undervaluation hypothesis is based on the argument that information asymmetry between insiders and shareholders can cause a company to be misvalued. If insiders trust that the stock is undervalued, the firm may repurchase stock as a signal to the market or investing in its own stock and get mispriced shares. This hypothesis implies that the market interprets the action as an indication that the stock is undervalued (in Dittmar, 1999). Because of the asymmetric information between managers and shareholders, announcements of share repurchase are considered to expose private information that managers have about the value of the company. The information/signalling hypothesis has three immediate implications: repurchase announcements should be accompanied by positive price changes; repurchase announcements should be followed (though not necessarily immediately) by positive news about profitability or cash flows; and repurchase announcements should be immediately followed by positive changes in the market s expectation about future profitability (Gustavo Grullon and Roni Michaely, 2002) Research Motivation How do firms finance their operations? What factors influence these choices? How do these choices affect the stock price? And how do firms finance their operations over the firm s life cycle? These are important questions that have motivated the researcher to conduct this research. Based on theories explanation above, we understand that a firm s characteristics, cost and benefit, market reaction, and a firm s life cycle influenced the choice of a firm s capital structure, and it is important for the manager of a firm to understand the theory of capital structure. There have been many previous studies which examine one of thatfactors in influencing the choice of a firm s capital structure; however, there have been few that analyse all factors on the whole in affecting the choice of a firm s capital structure. Based on that motivation, through this research, we examine those factors on the choice of a firm s capital structure by formulating research hypotheses. We examine all the following issues, the determinants of capital structure of the firms in Indonesia, study how firms in manufacturing sector raise capital for investments; investigate what will happen to the firm s stock 15

16 price if firms issue new debt, issue new equity, and issue debt to repurchase equity; and examine how firms in Indonesia raise capital for investments over their life cycle stages. Our motivation to test Hypothesis 1 is that the test of determinants of capital structure of the firms in manufacturing sector in Indonesia is important as these firms have different characteristics. We test it on the basis of the pecking order theory and the trade-off theory. The trade-off theory and the pecking order theory imply that growth opportunities and asset tangibility have a positive relationship with the debt ratio, while the relationship between risk (earnings volatility) and debt ratio is negative. The pecking order hypothesis implies that a firm s profitability and size have a negative relationship with the level of debt. Under trade-off theory size and profitability have a positive relationship with the debt ratio. The important thing when examining hypothesis 2 in this research, is that we would like to test how firms in the manufacturing sector in LQ45 index finance the firms deficit, as these firms are experiencing financial deficit over the period of time (see table). Our analysis is related to Shyam-Sunder and Myers (1999) and Frank and Goyal (2003), who propose to test the standard pecking order using a regression of debt issued on the financing deficit. The argument is that the original pecking order predicts that firms issue debt whenever their internal cash flows are insufficient to finance real investments (and other uses of funds such as dividends). The financing deficit, i.e. uses of funds minus internal sources of funds, therefore drives debt issuance. Our motivation to test hypothesis 3 is that, as empirical evidence on the effect of capital structure choice on stock market reaction is limited, hence, we examine the relationship between capital structure and stock price, based on the pecking order theory, the trade-off theory, the signalling theory, and asymmetric information. Based on signalling through capital structure, the markets normally react favourably to moderate increases in leverage and negatively to a fresh issue of equity. Under the trade-off theory, firms will only take actions if they expect benefits. An implication of the theory is that the market reaction to both equity and debt securities will be positive. The market response to a leverage change could be either good news or bad news. It is good news if the firm issues securities to take advantage of a promising new opportunity that has not previously been anticipated. It might be bad news if the firm issues securities because the firm actually needs more resources than anticipated to conduct operations. The pecking order theory is usually interpreted as predicting that securities with more adverse selection (equity) will result in a more negative market reaction. Securities with less adverse selection (debt) will result in less negative or no market reaction. Meanwhile, the explanations for buybacks are based on the information/signalling hypothesis that has three immediate implications: repurchase announcements should be accompanied by positive price changes; repurchase announcements should be followed (though not necessarily immediately) by positive news about profitability or cash flows; and repurchase announcements should be immediately followed by positive changes in the market s expectation about future profitability. The most interesting part of this research is testing hypothesis 4. We examined capital structure choices over the firm s life cycle as our sample consists of 10 mature firms and 16 growth firms, where we define mature firms as firms that have 6-year dividend payment periods. Frank and Goyal (2003) argue that the support for the standard pecking order in Shyam-Sunder and Myers depends critically on their sample selection. Shyam-Sunder and Myers consider 157 firms that have no reporting gaps in their statement of cash-flows from 1971 to Frank and Goyal (2003) show that the results do not extent to an unbalanced sample, i.e. when reporting gaps 16

17 are allowed and to the time period from 1990 to Frank and Goyal (2003) argue that the sample selection of Shyam-Sunder and Myers picks large mature firms and that the standard pecking order is not a good description of the capital structure decisions for small, young firms in their larger sample. Hence, it is important to examine capital structure choices over firm life cycle. Therefore, we then construct the following variables for our analysis: book leverage, market leverage, net equity issued, net debt issued, financing deficit, stock price, tangibility, profitability, risk, growth, and size. We first classify firms into two cohorts according to their life cycle stage, namely, firms in their growth stage and firms in their mature stage. We then focus on the pecking order theory of financing proposed by Myers (1984) and Myers and Maljuf (1984). This theory is based on asymmetric information between investors and firm managers. Due to the valuation discount that less-informed investors apply to newly issued securities, firms resort to internal funds first, then debt and equity last to satisfy their financing needs. In the context of a firm s life cycle, we expect that asymmetric information problems are more severe among young, growth firms compared to firms that have reached maturity. Hence, the theory predicts that younger, fast-growth firms should be following the pecking order more closely. Our research findings could be the comparison to the findings of previous research and theories. This is how this thesis adds to the scientific literature. 1.2 Problem Identification In order to keep developing, the firms in the manufacturing sector need to finance their financial deficit or even new projects, hence it is important to firms to implement the theories of capital structure described earlier in choosing carefully their capital structure for financing the investment. Firm managers can consider the cost and benefit of each capital structure preferences based on the theories as each preference will affect market reaction which is reflected by the firm s stock price valued by the market and the firm s life cycle which influences the choice of the firm s capital structure. Table 1.1. GDP Sectors (in Billion Indonesian Rupiah, IDR) Sector Agriculture Mining Manufacturing Industry Electricity Building Trade Transportation Financial Institutions Services Sources: Indonesia Stock Exchange, IDX (2011) We choose firms in the manufacturing sector as our sample because the sector has grown faster than any other sector in the Indonesian economy in However, the GDP decreased significantly in 1998, but within the years , the GDP was unstable. For instance, in 1994 (see table 1.1), the GDP of the sector was only By 1994, the sector had increased to In 1996, the sector increased to and in 1997 reached the level of (IDX, 2011). 17

18 Table 1.2a. GDP Sectors (%) Sector Agriculture 1,3 2,7 1,7 0,6 3,2 Mining 2, ,6 1.0 Manufacturing Industry 11,4 3,8 6,2 4,3 5.3 Electricity 3,0 8, ,4 8,9 Building 36, ,0 5,5 Trade 18,2 0,1 5,7 5,1 3.9 Transportation 15,1-0, ,5 8,4 Financial Institutions 26,6-7,5 4,7 3,0 6,4 Services 3,8 1,9 2,2 2,0 3,8 Sources: Indonesia Stock Exchange (2011) Table 1.2b. GDP Sectors (%) Sector Agriculture 3,8 2,8 2,7 3,4 3,5 Mining -1,4-4,5 3,2 1,7 2,0 Manufacturing Industry 5,3 6,4 4,6 4,6 4,7 Electricity 4,9 5,3 6,3 5,8 10,4 Building 6,1 7,5 7,5 8,3 8,6 Trade 5,4 5,7 8,3 6,4 8,5 Transportation 12,2 13,4 12,8 14,4 14,4 Financial Institutions 6,7 7,7 6,7 5,5 8,0 Services 4,4 5,4 5,2 6,2 6,6 Sources: Indonesia Stock Exchange (2011) In 1998, the contribution of manufacturing industries to total GDP was -11.4%, and increased to 3.8% in By 2000, the sector had increased to 6.2 percent of GDP. In 2001, the sector decreased to 4.3 percent of GDP. In 2002 and 2003, the contribution of manufacturing industries to total GDP was 5.3%, and increased to 6.4% in However, in 2005, the contribution of manufacturing industries to total GDP was decreased to 4.6% in 2005 and 2006, and increased to only 4.7% in Meanwhile, the total export in 1980 of manufacturing industries was 2.3% (World Bank, 2003). The export from manufacturing industries continued to increase and by 1990 it was accounted for 35.5% of the total export in that year. In 2001 more than 56% of the total export was from manufacturing industries (Indonesia Statistical Centre, 2003). Therefore, firms in the manufacturing sector of the LQ45 Index need to implement the theories of capital structure to choose their capital structure for financing the investment, so that they could increase the production and profit. Additionaly, we choose the LQ45 Index as the index represents 45 of the most liquid stocks. To date, the LQ45 Index covers at least 70% of market capitalisation and transaction values in the Regular Market and it consists of 45 stocks that have passed the liquidity and market capitalisation screenings (Indonesia Stock Exchange, 2011). 18

19 1.3 Research Questions The research is going to answer the following major and minor research questions: Major Research Questions Our major research questions are as follow: 1. What are the determinants of capital structure of the firms in the manufacturing sector in Indonesia? 2. How do firms in the manufacturing sector in Indonesia raise capital for investments, internally or externally (with debt, equity, or debt to repurchase equity)? 3. Does debt policy matter? 4. In the context of firm s life cycle, can we expect that growth [and small] firms follow the pecking order theory more closely than mature [and large] firms? Minor Research Questions Our minor research questions are as follow: 1. What are the determinants of capital structure of the firms in the manufacturing sector in Indonesia? a. As implied by the trade-off theory and the pecking order theory, do growth opportunities have a positive relationship with the debt ratio? b. As in the pecking order hypothesis, does the firm s profitability have a negative relationship with the level of debt? And as implied by the trade-off theory, does the firm s profitability have a positive relationship with the debt ratio? c. In accordance with the pecking order theory and trade-off theory, is there a negative relationship between risk (earnings volatility) and debt ratio? d. As suggested by the trade-off theory, does size have a positive relationship with the debt ratio? And as suggested by the pecking order theory of the capital structure, is there a negative relationship between the level of debt and the size of the firm? e. In accordance with the trade-off theory, is there a positive relationship between the asset tangibility and the level of debt? 2. How do firms in the manufacturing sector in Indonesia raise capital for investments, internally or externally (with debt, equity, or debt to repurchase equity)? 3. Does debt policy matter? Based on the asymmetric information, the firms use equity financing only as the last resort and based on signalling theory, the markets normally react favourably to moderate increases in leverage and negatively to a fresh issue of equity. 19

20 (a) If a firm issues new debt, what will happen to the firm s stock price? (b) If a firm issues new equity, what will happen to the firm s stock price? (c) If a firm issues debt to repurchase equity, what will happen to the firm s stock price? 4. In the context of firm s life cycle, can we expect that growth [and small] firms follow the pecking order theory more closely than mature [and large] firms? 1.4 Research Objectives Based on research questions, the objectives of this research are to: 1. Determine the determinants of capital structure of firms in the manufacturing sector in the Indonesian capital market. a. Investigate the relationship between growth and debt ratios as implied by the trade-off theory and the pecking order theory. b. Examine the relationship between a firm s profitability and debt ratios as implied by the trade-off theory and the pecking order theory. c. Determine the relationship between risk (earnings volatility) and debt ratios as implied by the trade-off theory and the pecking order theory. d. Investigate the relationship between size and debt ratios as suggested by the trade-off theory and the pecking order theory. e. Analyse the relationship between asset tangibility and debt ratios as implied by the trade-off theory. 2. Investigate how firms in manufacturing sector raise capital for investments, internally or externally (with debt, equity, or debt to repurchase equity). 3. Examine whether debt policy matters: (a) Analyse if a firm issues new debt, what will happen to the firm s stock price. (b) Analyse if a firm issues new equity, what will happen to the firm s stock price. (c) Analyse if a firm issues debt to repurchase equity, what will happen to the firm s stock price. 4. Examine in the context of firm s life cycle, do growth [and small] firms follow the pecking order theory more closely than mature [and large] firms. 1.5 Scope and Limitation of the Study The scope of the study is to investigate the determinants of capital structure of the firms in the manufacturing sector in Indonesia, examine how firms in the manufacturing sector raise capital for investments, internally or externally (with debt, equity, or debt to repurchase equity), investigate if debt policy matters, what will happen to the firm s stock price if firms issue new debt, issue new equity, and issue debt to repurchase equity. Finally, we examine in the context of 20

21 firm s life cycle, do growth [and small] firms follow the pecking order theory more closely than mature [and large] firms. Manufacturing companies that exist throughout the 13-year period with no missing data are included in the study. Data availability is a major limitation in capital structure studies in emerging capital markets. We use data of the Indonesia Stock Exchange Main Board companies, with the selected time period of to capture the differences in economic conditions of the Indonesian economy. To enlighten it, we explain those periods that describe the differences in economic conditions. Before the Crisis Period (Before 1997) Before the economic crisis triggered by the financial crisis in mid 1997, Indonesia was among the few developing countries which were rated as highly successful in its development. Within thirty years, from 1965 to 1995, GDP per capita in real terms grew on average by 6.6% annually (World Bank 1997). The role of manufacturing industry in GDP experienced a significant increased, from 7.6% in 1973 to nearly 25% in Crisis Period ( ) In 1995 Indonesia was still enjoying an economic growth of 8.2%, later in 1996, or the last year before the crisis happened, it still grew with 7.8%, and in 1997 dropped to 4.9%. So, until 1997, the year of the crisis, at least, economic growth still remained positive despite showing a declining trend. The crisis that began with the fall of the Thai Baht in July 1997, then gave a direct result on the value of IDR which depreciated exponentially, from Rp2.400 per Dollar in mid-1997 to Rp per Dollar in June The decline in food production triggered high inflation in 1998, added pressuring on foreign exchange reserves that have already declined. In 1998, when the crisis reached its peak, Indonesia's economic growth contracted by 13.6% and other macroeconomic indicators showed worsening values, such as inflation which increased to 77.6%. The crisis that hit Indonesia since mid 1997 has gradually decreased and by the end of the reporting year 1998/99 Indonesian economy began to show improvement. Inflationary pressures continued to decline from October 1998 onwards, so that the annual inflation rate had reached 82.4% in September 1998, and was successfully reduced to 45.4% at the year-end report. The success in reducing inflationary pressures reflected in the strengthening trend of the IDR In 1999, inflation rate was under control, from almost 80% in 1998 to 2% in the following year, With these conditions, the interest rate could drop from about 80% to 11-12%. By mid-1999, the economic crisis in Indonesia had surpassed its lowest point and began to grow again. Throughout the year, the economy grew slightly with an increase in GDP of 0.3%. Entering early 2000, the process of economic recovery had begun to appear since the third quarter of Monetary stability was also controllable, as reflected in the achievement of low inflation and stronger exchange rate until the end of Economic growth was increasing higher than forecasted to 4.8%. The IDR tended to weaken and volatile since May Meanwhile, pressure on the inflation rate increased and inflationary pressures also emerged as a result of the weakening of the IDR. 21

22 During the 2001, economic and monetary conditions in general showed a deteriorating trend. Worsening the economic and monetary conditions, among others, indicated by the slowing economic growth, a weakening exchange rate, and high inflation pressures. During 2001, Indonesia's economy grew only by 3.3%, the exchange rate depreciated by 17.7% so that to achieve an average of Rp per USD Dollar, and CPI inflation reached 12.55%. During 2002, the general economic condition in Indonesia showed a positive growth which was indicated by more stable macroeconomic conditions. Overall, in 2002, the exchange rate appreciated significantly by 10.10% so as to achieve an average of Rp per US Dollar. These stable monetary conditions have affected the level of CPI inflation during 2002, experiencing a declining trend to reach 10.03%. Overall, during 2002 the Indonesian economy only grew by 3.7%. In 2003, to face the challenges, the Government and the Bank of Indonesia have taken a series of policies to encourage the process of economic recovery while maintaining macroeconomic stability. In the process, various policies have contributed significantly in supporting the achievement of stable macro economic conditions during 2003, which indicated by the strengthening of the IDR and declining of inflation rate. The year 2004 brang hope, optimism, as well as a new challenge. In 2004, macroeconomic stability maintained, international confidence increased, and clarity of the economic agenda eached The year 2005 was a dynamic and challenging one for the economy of Indonesia. On the average, the Rupiah reached Rp per U.S. Dollar during 2005, or a depreciation by 8.6% compared to an average of Meanwhile, the CPI inflation, which until the third quarter of 2005 was recorded at 9.1% (year on year, yoy) had increased to 17.1% (yoy) in late Overall economic growth in Indonesia in 2005 reached 5.6% or achieved an increase of 5.1% from the previous year. Entering the beginning of 2006, Indonesia economic conditions are still very influenced by the rising of fuel prices (fuel) and high interest rates. Inflation rate of consumer price index (CPI) which is very high in early 2006 reached 17.03% (yoy) gradually decreased to 6.60% (yoy) in late 2006 and maintained stability in the rupiah. With inflation and interest rates which gradually declined, since the beginning of the second half of 2006, the economy grew in the good trend so as the overall in 2006, growth reached 5.5% (yoy), slightly lower than the previous year. Entering 2007, Indonesia's economy to regain macroeconomic stability. The Rupiah, in the second half of 2007 was depreciated significantly and reached the weakest level in August 2007, with a monthly average of Rp 9372 per U.S. Dollar. Maintained macroeconomic stability kept a high economic growth in 2007, and even reached the highest level in the post-crisis period, namely 6.32%. 1.6 Expected Contribution By conducting this research, we expected some contributions for the firms. In this research, the purpose of our research will not be to produce a theory that is generalisable to all populations. Our objective is trying to explain what is happening in the Indonesian capital market with manufacturing firms of the LQ45 Index, regarding how firms finance their operations. What factors influence the choices of capital structure? How do these choices affect the stock price? And 22

23 how do firms finance their deficit over a firm s life cycle? The findings of this study will lead firms to make the decision of choosing capital structure by considering the firm s characteristics, market reaction reflected by stock price, and the life cycle stage of the firm. 1.7 Organisation of the Study Figure 1.1. Organisation of the Study CHAPTER 1. Introduction CHAPTER 2. An Overview of Firm s Capital Structure in Indonesia CHAPTER 4. Conceptual Framework CHAPTER 3. Literature Review CHAPTER 5. Research Methodology CHAPTER 6. Presentation of Data and Analysis of Results Appendices CHAPTER 7. Conclusion, Recommendations, and Suggestion for Further Research The structure of the thesis is illustrated in the above figure. In more detail, chapter 1 provides an introduction consisting of the background of the research, problem identification and research problems, research questions, research objectives, and significance of study, which include scope and limitations of the study, expected contribution, and organisation of the study. The work in chapter 2 reflects an overview of a firm s capital structure in Indonesia. Chapter 3 explains literature review. Chapter 4 provides conceptual framework and research methodology. This chapter clearly identifies and analyses gaps in the literature as well as it demonstrates the theory from which we derive each hypothesis, and identify dependent and independent variables and link these to relevant research questions and respective hypotheses. Chapter 5 analyses research methodology. Chapter 6 should integrate both presentation of data and analysis of results. Chapter 7 draws the conclusions, recommendations, and suggestion for further research. Finally, the appendix will give a depiction of statistical information gathered during the research, and figures of the firms. 23

24 2. AN OVERVIEW OF THE CAPITAL STRUCTURE OF INDONESIAN MANUFACTURING FIRMS 2.1. Indonesian Capital Market The capital market plays an important role in the economy of a country, including Indonesia, because it serves two functions at the same time. First, the capital market serves as an alternative for a company's capital resources. The capital gained from the public offering can be used for the company's business development, expansion, and so on. Second, the capital market serves as an alternative for public investment. People could invest their money according to their preferred returns and risk characteristics of each instrument History of Indonesia Stock Exchange Below is the brief history of the Indonesia Stock Exchange. The first Stock Exchange in Indonesia was built in Batavia (currently known as Jakarta) in December The Batavia Stock Exchange was closed during the years It was re-opened in 1925 and new stock exchanges were established in Semarang and Surabaya. However, between 1919 and 1924, the Indonesia Stock Exchange (IDX) was still closed. The Jakarta Stock Exchange (JSX) was re-closed during the years On August 10, 1977, the Exchange was re-activated by President Soeharto. It was supervised under the management of the Capital Market Supervisory Agency (Badan Pengawas Pasar Modal, or BAPEPAM). The re-activation of the capital market was also marked by the going public of PT Semen Cibinong as the first issuer listed in the JSX. July 10th is celebrated as the anniversary of the Capital Market in Indonesia. In , the activity of stock trading in the JSX was dull. There were only 24 listed companies in the JSX. Most people preferred to invest their money in banks rather than the capital market. December Package 1987) was issued to give ways for companies to go public and for foreign investors to invest their money in Indonesia in In , deregulation packages in banking and capital market were made. The JSX welcomed foreign investors. The activities of the JSX were improving. On June 16, 1989, the Surabaya Stock Exchange started to operate and was managed by the Surabaya Stock Exchange Inc. On July 13, 1992, the JSX was privatised, and this date is celebrated as the anniversary of the Jakarta Stock Exchange. The JSX introduced its computerized Jakarta Automatic Trading System (JATS) on May 22, On November 10, 1995, the Government of Indonesia issued Regulations No. 8 year 1995 on the capital market. This regulation was effective from January The JSX started to implement the remote trading system in In 2007, the Surabaya Stock Exchange was merged into Jakarta Stock Exchange. As a result, the JSX changed its name into the Indonesia Stock Exchange Stock Price Index in the Indonesian Capital Market In order to give more complete information on the stock exchange development to the public, the Indonesian Stock Exchange (IDX) has spread the indicators of the stock price 24

25 movement through the printed and electronic media. One indicator of the stock price movement is the Stock Price Index. At present, the JSX has 9 constituent Stock Price Indices and 10 sectors: Composite Stock Price Index (CSPI), Main Board Index (MBX), Kompas 100, Liquid 45 (LQ45), Jakarta Islamic Index, Development Board Index (DBX), Indonesian Securties Rating Agency (PEFINDO25), BISNIS-27, and Sustainable Responsible Investment-Indonesian Biodiversity Foundation. The sectors include mining, agriculture, consumers, miscellaneousindustry, manufacture, infrastructure, finance, trade, basic-industry, and property. The following indices are guidelines for investors to make stock investment in the Indonesian capital market. 1. The Composite Stock Price Index (CSPI), the index that uses all of the Companies Listed as a component of index calculation. The Composite Stock Price Index (CSPI) was introduced the first time on April 1 st, 1983 as an indicator of the movement of all listed stock prices in the JSX, for both the regular and the preferred stocks. The base day for the CSPI s calculation is on August 10 th, At that date, the index was determined at 100, and the listed number of stocks at that time was thirteen. 2. The JSX LQ45 Index was created to provide the market with an index that represents 45 of the most liquid stocks. To date, the LQ45 Index covers at least 70% of the market capitalisation and transaction values in the Regular Market. The LQ45 Index of historical calculation was defined on July 13, 1994, with a base value of 100. The index consists of 45 stocks that have passed the liquidity and market capitalisation screenings. 3. The Jakarta Islamic Index was launched on July 3, The index consists of 30 stocks that have passed the selection under the direction of the Sharia Supervisory Board of the Majelis Ulama Indonesia. Stocks from listed companies with business activities that comply with the Islamic sharia can be included into the index. 4. The Kompas 100 Index is an index consisting of 100 shares of Listed Companies that are selected, based on considerations of liquidity and market capitalisation, in line with predetermined criteria. 5. The Index BUSINESS-27 is a collaboration between the IDX and Bisnis Indonesia Daily. The Stock index Listed Companies are selected based on fundamental criteria, technical or liquidity of transactions and accountability and corporate governance. 6. The PEFINDO-25 Index is a collaboration between the BEI and the PEFINDO rating agencies, which is intended to provide additional information for investors, especially for the shares of small and medium-sized listed companies (Small Medium Enterprises/SME). 7. The Sustainable Responsible Investment-KEHATI Index is the index established for cooperation between the BEI and the Indonesian Biodiversity Foundation (KEHATI). This index is expected to provide additional information to investors who want to invest in stocks that have excellent performance in encouraging sustainable business, and have awareness of the environment and run good corporate governance. 8. The Main Board Index (MBX) and the Development Board Index (DBX). On July13 th, 2000, the JSX launched a new rule on stock listing: the Two Board Listing System. This system is implemented to stimulate the Indonesian Capital Market and also to recover public confidence for the Exchange through the arrangement of good corporate governance. 9. Sectoral indices, the index that uses all the Listed Companies included in each sector. Today there are 10 sectors in the IDX, namely agriculture; mining;, primary industrie;, miscellaneous industry;, consumer goods; property; infrastructure; finance; trade and services; and manufacture. 25

26 Description of the LQ45 Index We chose the LQ45 Index as our population as LQ45 Index consists of 45 stocks with high liquidity. The Indonesia Stock Exchange regularly monitors the performance progress of the stock components which are included in the calculation of the LQ45 index. Every three months an evaluation on the movement sequence of the shares is conducted. Replacement shares will be conducted every six months, i.e. at the beginning of February and August. Therefore, we chose the LQ45 index as our population in this research. Since its launch in February 1997, the primary measure of liquidity transaction is the value of transactions in the regular market. In accordance with market developments, and to sharpen further the criteria of liquidity, since the review in January 2005, the number of trading days and the frequency of transactions has been included as a measure of liquidity. Thus, the criterium of stock that is to be included in the calculation of the LQ45 Index is as follows: 1. Has been listed on the Stock Exchange at least 3 months 2. Log in 60 stocks based on the value of transactions in the regular market 3. Of the 60 stocks, 30 stocks with the largest transaction value will automatically be included on the calculation of the index LQ To get 45 shares 15 shares will be selected again by using the criteria of day transaction in regular market, frequency of transaction in regular market and market capitalisation. 15 stocks selection methods are the following: a. 30 of the remaining stocks, 25 stocks are selected based on transactions day in the regular market. b. 25 of the stocks 20 stocks will be selected based on the frequency of transactions in the regular market. c. 20 of the stocks will be selected 15 stocks based on market capitalisation, so it will get 45 shares for calculation of the LQ45 Index. 5. In addition to considering the liquidity criteria and market capitalisation mentioned above, will be seen also the financial condition and prospects of the company's growth Characteristics of the Research Sample We constructed two samples of firms according to their life cycle stage, namely, firms in their growth stage and firms in their mature stage. Bulan and Yan (2009) defined the growth stage as the first six-year-period after the year of the firm s initial public offering (IPO). They treated the IPO as the starting point of the growth stage (or the new growth stage). Hence, we follow them to identify the growth stage. We took Grullon, Michaely and Swaminathan (2000), DeAngelo, DeAngelo and Stulz (2005) and Bulan, Subramanian and Tanlu as the references (2007) who found that firms initiated dividends were mature firms. Thus, we identified firms in their mature stage by their dividend history. Meanwhile, we defined six years old or younger as young firms and seven years or older as old firms. We followed Bulan and Yan (2007) and Evans (1987) to set the length of each stage to be 6 years. Finally, we defined "small" as firms with total assets of less than $150 million, and large firms that have total asset of more than $150 millions (Hufft, JR), it equals to IDR 1,081, or 1,086,

27 1. Astra International Tbk (ASII) ASII is a company engaged in the sector of miscellaneous industry, by the industrial sub sector of Automotive and Components. It was established on February 20, 1957 and was listed at the IDX on April 4, Its IPO price was IDR In the period of 1996 to 2009 the price was very volatile. In July 2010 the price was increased significantly to IDR The average total asset of ASII in the year 1994 to 2007 is 30,934,935.6 million. Hufft, JR defines a small firm as the one that has total assets of less than USD 150 million. That means a firm with total assets of more than USD 150 million is considered a large firm. Hence ASII is a large firm. The average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and While the average short-term, long-term, total, and its market leverage are , , , and Bulan, Subramanian, and Tanlu (2007) find that firms that initiate dividends are mature firms. Thus Bulan and Yan (2007) identify firms in their mature stage by their dividend history. We take Bulan and Yan (2007) the references to construct the sample, deeming 6-year dividends payment periods as the mature stage of a firm s life cycle. This 6-year requirement is to ensure that whatever reason for the dividend omission, the firm has fully recovered and re-emerged as a regular dividend payer. ASII has paid the dividend during 2002 to 2007 and 1994 to 1996, thus it is categorised as a mature firm. 2. Astra Otoparts Tbk (AUTO) AUTO is a company engaged in the sector of miscellaneous industry, by the industrial sub-sector of automotive and components. The company was established on September 20, 1991 and was listed at the IDX on October 1, Its IPO price was IDR 575. In 1998 its price had been decreased to IDR 375. During 1999 to 2002 its price was slightly volatile. The total assets of AUTO in the period of 1994 to 2007 was IDR million. Thus we take AUTO as a small firm. The average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and , AUTO was listed in 1993 and has consecutively paid the dividend for seven years during 2001 to So we consider AUTO as a mature firm. 3. Polychem Indonesia Tbk (ADMG) ADMG is a company engaged in the sector of miscellaneous industry, by the industrial sub-sector of textile and garment. It was established on April 25, 1986 and was listed at the IDX on October 20, Its IPO price was IDR 4250 and the price was slightly volatile during 2001 to In August 2010, its share price was decreased significantly to IDR 164. The average total assets of this company during 1994 to 2007 were IDR 6,191, million or more than USD 150 million, so it is a large firm. Its average values of the variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and As ADMG has not paid dividend in the period of , or in the 6-year period, hence, it was categorised as a growth firm. 27

28 4. Barito Pacific Tbk (BRPT) BRPT is a company engaged in the sector of basic industry and chemicals, by the industrial sub-sector of chemicals. It was established on April 4, 1979 and was listed at the IDX on October 1, Its IPO price was IDR 7200 and the price was very volatile during 1996 to In 2001 it hit the lowest price of IDR 50, but in July 2010, it bounced to IDR But still it is lower than its IPO price. We take BRPT as a large firm since the average total assets during 1994 to 2007 were IDR 4,107, million or over USD 150 million. The average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and BRPT has paid dividend to shareholders in , thus, it is categorised as a growth firm. 5. Budi Acid Jaya Tbk (BUDI) BUDI is a company engaged in the sector of basic industry and chemicals, by the industrial sub-sector of chemicals. It was established in Jan 15, 1979 and was listed at the IDX on May 8, Its IPO price was IDR 3000 and the price during 199 to 2000 was very volatile. In August 2010 it was decreased significantly to IDR 335. We take this company as small firm since its average total assets in 1994 to 2007 were IDR 496, million or less than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth, are , , , , and The average short-term, long-term, total, and its market leverage are , , , and BUDI has paid dividend in 1994 to 1996, 1999, and 2006 to 2007, but it was not paid in the six year period consecutively thus, it is categorised as a growth firm. 6. Charoen Pokphand Indonesia Tbk (CPIN) CPIN is a company engaged in the sector of basic industry and chemicals, by the industrial sub-sector of pet food. It was established on January 7, 1973 and was listed at the IDX on March 18, The IPO price was IDR 5100 and the price was quite volatile in 1996 to 2000 and in 2003 to But in August 2010, it was increased to IDR 6450 million, or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth, are , , , , and CPIN is a growing firm since it paid the dividend not in 6 consecutive years in 1994 to 1996, and Dankos Laboratories Tbk (DNKS) DNKS is a company engaged in the sector of pharmaceuticals. It was established on March 25, 1974 and was listed at the IDX on November 13, The IPO price was IDR The price was quite volatile in 1996 to 2002 and hit the lowest price of IDR 250. DNKS is a small firm since its average total assets in 1994 to 2007 was IDR 377, million or less than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth, are , , , , and The average short-term, long-term, total, and its market leverage are , , , and DNKS is a growing firm since it did not pay the dividend in 6 consecutive years. 28

29 8. Fajar Surya Wisesa Tbk (FASW) FASW is a company engaged in the sector of basic industry and chemicals, by the industrial sub-sector of pulp and paper. It was established on June 13, 1987 and was listed at the IDX on December 19, The IPO price was IDR 3200 and it was slightly volatile in 1996 to In August 2010 it was IDR FASW is a large firm since its average total assets during 1994 to 2007 were IDR 1,811, million, or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth, are , , , , and The average short-term, long-term, total, and its market leverage are , , , and FASW is categorised as a growing firm since it paid the dividend only for 1994, 1995, and Gudang Garam Tbk (GGRM) GGRM is a company engaged in the sector of consumer goods industry, by the industrial sub-sector of tobacco manufacturers. It was established on June 26, 1958 and was listed at the IDX on August 27, The IPO price was IDR and during 1995 to 2007 the price was quite stable. In July 2010, the price was increased significantly, almost triple, to IDR GGRM is large firm since its average total assets in 1994 to 2007 were IDR 10,846, million or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth, are , , , , and The average short-term, long-term, total, and its market leverage is , , , and GGRM is a mature firm since it has paid the dividend in 1994 to 1998, 2000 to 2004, and 2006 to Gajah Tunggal Tbk (GJTL) GJTL is a company engaged in the sector of miscellaneous industry, by the industrial sub-sector of automotive and components. It was established on August 24, 1951 and was listed at the IDX on May 8, The IPO price was IDR 5500 and during 1996 to 2007 the price was quite stable. But in August 2010 the price decreased significantly below its IPO price to IDR GJTL is a large firm since it had total assets of IDR 9,353, million or more than USD 150 million during 1994 to Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and GJTL paid dividend in 1994 to 1996 and 2005 to 2007, but since it was not paid in 6 consecutive years, we categorise this firm as a growing firm. 11. Hanjaya Mandala Sampoerna Tbk (HMSP) HMSP is a company engaged in the sector of consumer goods industry, by industrial subsector of tobacco manufacturers. It was established on March 27, 1905 and was listed at the IDX on August 15, The IPO price was IDR and its price was quite volatile during 1996 to However, the price was increased significantly to IDR in August HMSP is a large firm since its average total assets in the year of 1994 to 2007 was IDR 5,418, million or over the USD 150 million. Its average value of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , 29

30 , and The average short-term, long-term, total, and its market leverage are , , , and HMSP is a mature firm. It paid the dividend in 1994 to 1996 and 1999 to Indofood Sukses Makmur Tbk (INDF) INDF is a company engaged in the sector of consumer goods industry, by the industrial sub sector of food and beverages. It was established on August 14, 1990 and was listed at the IDX on July 14, The IPO price was IDR 6200 and during 1996 to 2007 the price was quite volatile. It reached the lowest price of IDR 625 in In July 2010 it reached IDR 4625, but still it was below the IPO price. INDF is a large firm since its average total assets in 1994 to 2007 was IDR 11,630, million or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and INDF is a mature firm since it paid the dividend 6 years in a row in 1994 to 1996 and in 2000 to Indorama Synthetics Tbk (INDR) INDR is a company engaged in the sector of miscellaneous industry, by the industrial sub-sector of textile and garments. It was established on April 3, 1974 and was listed at the IDX on August 3, The IPO price was IDR and during 1996 to 2002 the price was slightly volatile. In August 2010 the price decreased significantly to IDR 640. INDR is a large firm since its average total assets in 1994 to 2007 was IDR 3,472, million, or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and INDR is a growing firm since it did not pay the dividend in 6 consecutive years. 14. Indah Kiat Pulp and Paper Tbk (INKP) INKP is a company engaged in the sector of basic industry and chemicals, by the industrial sub-sector of pulp and paper. It was established on December 7, 1976 and was listed at the IDX on July 16, The IPO price was IDR 10,600 and during 1996 to 2007 the price was slightly volatile. In August 2010 the price decreased significantly to IDR 640 INKP is a large firm since its average total assets in 1994 to 2007 was IDR 38,541, million or more than USD 150 million. Its average value of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and Since INKP did not pay dividend in 6 consecutive years, it is categorised as growing firm. 15. Indofarma Tbk (INAF) INAF is a company engaged in the sector of consumer goods industry, by the industrial sub-sector of pharmacy. It was established on January 2, 1996 and was listed at the IDX on April 30

31 17, The IPO price was IDR 250 and it was quite stable from 2001 to 2002 and from 2006 to INAF is a small firm since its average total assets in 1994 to 2007 was IDR 549, million or less than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and INAF has paid dividend in , thus we decide to categorise it as a growth firm. 16. Indocement Tunggal Prakasa Tbk (INTP) INTP is a company engaged in the sector of basic industry and chemicals, by the industrial sub sector of cement. It was established on January 16, 1985 and was listed at the IDX on December 5, The IPO price was IDR 10,000 and during 1998 to 2007 the price was quite volatile. In July 2010 the price increased significantly to IDR INTP is a large firm since its average total assets in 1994 to 2007 was IDR 6,510, million or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and INTP has paid dividend in , thus we decide to categorise it as a growth firm. 17. Kalbe Farma Tbk (KLBF) KLBF is a company engaged in the sector of consumer goods industry, by the industrial sub sector of pharmacy. It was established on September 10, 1966 and was listed at the IDX on July 30, Its IPO price was IDR 7800 and it was slightly volatile in 1996 to In July 2010 the price decreased significantly to IDR KLBF is a large firm since its average total assets in 1994 to 2007 was IDR 2,564, million or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , , and KLBF is categorised as a growing firm since it did not pay the dividend in 6 consecutive years. 18. Komatsu Indonesia Tbk (KOMI) KOMI is a company engaged in the sector of miscellaneous industry, by the industrial sub sector of machinery and heavy equipment. It was established on December 13, 1982 and was listed at the IDX on October 31, 1995 but delisted on January 2, The IPO price was IDR 2100 and it was slightly volatile in 1996 to KOMI is a small firm since its average total assets in 1994 to 2007 was IDR 323, million or less than USD 150 million. Its average values of variable total assets in 1994 to 2007 that consists of profitability, tangibility, size, risk, and growth were , , , , and The average short-term, long-term, total, and its market leverage are , , , and KOMI has paid dividend in , and 1999, thus we decide to categorise it as a growth firm. 31

32 19. Kimia Farma Tbk (KAEF) KAEF is a company engaged in the sector of consumer goods industry, by the industrial sub sector of pharmacy. It was established on January 23, 1969 and was listed at the IDX on July 4, The IPO price was IDR 200 and it was quite stable from 2001 to 2002 and from 2006 to KAEF is a small firm since its average total assets in 1994 to 2007 was IDR 914, million or less than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and KAEF is a mature firm as it paid dividend in 6 consecutive years from 2001 to Bentoel International Investama Tbk (RMBA) RMBA is a company engaged in the sector of consumer goods industry, by the industrial sub sector of tobacco manufacturers. It was established on January 19, 1979 and was listed at the IDX on March 5, The IPO price was IDR 3380 and during 1998 to 2002 the price was quite volatile. In August 2010 the price increased significantly to IDR 520. RMBA is a small firm since its average total assets in 1994 to 2007 was IDR 946, million or less than USD 150 million. Its average value of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and RMBA is a growing firm as it has not paid the dividend in 6 consecutive years. 21. Holcim Indonesia Tbk (SMCB) SMCB is a company engaged in the sector of basic industry and chemicals, by the industrial sub sector of cement. It was established on June 15, 1971 and was listed at the IDX on August 10, The IPO price was IDR 10,000 and the price is quite stable in 1996 to In July 2010 the price decreased significantly to IDR SMCB is a large firm since its average total assets in 1994 to 2007 was IDR 6,335, million, or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and SMCB has paid dividend in 1994, and 1996 to 1997, thus we decide to categorise it as a growth firm. 22. Semen Gresik Persero Tbk (SMGR) SMGR is a company engaged in the sector of basic industry and chemicals, by the industrial sub sector of cement. It was established on March 25, 1953 and was listed at the IDX on July 8, The IPO price was IDR 7000 and it was slightly volatile in 1996 to In 2006 it was surprisingly increased to IDR but in July 2010 it decreased to IDR SMGR is a large firm since its average total assets in 1994 to 2007 was IDR 5,729, million, or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , 32

33 , and The average short-term, long-term, total, and its market leverage are , , , and SMGR has paid the dividend but not in 6 consecutive years. So we categorise it as a growing firm. 23. Pabrik Kertas Tjiwi Kimia Tbk (TKIM) TKIM is a company engaged in the sector of basic industry and chemicals, by the industrial sub sector of pulp and paper. It was established on October 2, 1972 and was listed at the IDX on April 3, The IPO price was IDR 9,500 and it was quite volatile during 1996 to In August 2010 the price decreased significantly to IDR TKIM is a large firm since its average total assets in 1994 to 2007 was IDR 14,313, million or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , 0.711, and TKIM has paid dividend in 1994 to 1996, thus we decide to categorise it as a growth firm. 24. Tempo Scan Pacific Tbk (TSPC) TSPC is a company engaged in the sector of miscellaneous industry, by the industrial sub sector of pharmacy. It was established on May 20, 1970 and was listed at the IDX on June The IPO price was IDR 8250 and was quite volatile in 1996 to It decreased significantly to IDR 425 in from 1997 to TSPC is a small firm since its average total assets in 1994 to 2007 was IDR 1,056, million or less than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and TSPC is a growing firm since it did not pay the dividend in 6 consecutive years. 25. Unilever Indonesia Tbk (UNVR) UNVR is a company engaged in the sector of consumer goods industry, by the industrial sub sector of cosmetics and household. It was established on December 5, 1933 and was listed at the IDX on January 11, The IPO price was IDR 3175 and it was quite volatile in 1998 to In July 2010 the price increased significantly to IDR UNVR is a large firm since its average total assets from 1994 to 2007 were IDR 2,996, million, or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and UNVR has paid dividend in , thus we decide to categorise it as a mature firm. 26. Sumalindo Lestari Jaya Tbk (SULI) SULI is a company engaged in the sector of basic industry and chemicals, by the industrial sub sector of wood industry. It was established on April 14, 1980, and was listed at the IDX on March 21, The IPO price was IDR 9000 and the price was slightly volatile in 2003 to In August 2010, it decreased significantly to IDR

34 SULI is a large firm since its average total assets in 1994 to 2007 were IDR 1,401, million, or more than USD 150 million. Its average values of variable capital structure that consists of profitability, tangibility, size, risk, and growth are , , , , and The average short-term, long-term, total, and its market leverage are , , , and SULI has not paid dividend, thus we decide to categorise it as a growth firm. 2.3 Leverage Analysis Four debt ratios we used in this study are total leverage, short-term leverage, long-term leverage, and market leverage. These measures of debt ratios examine the capital employed and thus, best represent the effects of past financing decisions. The independent variables we chose are tangibility of assets, firm size, growth opportunities, profitability, and risk. The tangibility of assets represents the effect of the collateral value of assets of the firm s gearing level. There are various conceptions for the effect of tangibility on leverage decisions. If debt can be secured against assets, the borrower is restricted to using debt funds for specific projects. Creditors have an improved guarantee of repayment, but without collateralised assets, such a guarantee does not exist. Firm size provides a measure of the agency costs of equity and the demand for risk sharing. Firm size is likely to capture other firm characteristics as well (e.g., their reputation in debt markets or the extent to which their assets are diversified). For growth opportunities, the trade-off theory suggests that firms with more investment opportunities have less leverage because they have stronger incentives to avoid under-investment and asset substitution that can arise from stockholder-bondholder agency conflicts (Drobetz and Fix, 2003). Jensen s (1986) free cash flow theory similarly discusses that firms with more investment opportunities have less need for the disciplining effect of debt payments to control free cash flows. Meanwhile, profitability plays an important role in leverage decisions. Profitability is proxied by return on assets. ROA represents the contribution of the firm s assets on profitability creation. Profitability is a measure of earning power of a firm. The earning power of a firm is generally the basic concern of its shareholders. Finally, earnings volatility measures the variability of the firm's cash flows as a proxy for the costs of monitoring managers and of the risk of an insider's position. The use of longer time periods causes a significant loss of the sample size. Firms that have the highest short-term leverages are BRPT, AUTO, KAEF, CPIN, SULI, and ADMG. Firms that have the lowest short-term leverages are SMGR, TSPC, HMSP, INKP, INTP, BUDI, and KOMI. Firms that have the highest long-term leverages are ADMG, SMCB, SULI, INTP, GJTL, and INDF. Firms that have the lowest long-term leverages are GGRM, UNVR, KAEF, KOMI, INAF, and AUTO. Firms that have the highest market leverages are FASW, ADMG, INDR, TKIM, INKP, SMCB, CPIN, and INTP. Firms that have the lowest market leverages are HMSP, RMBA, UNVR, GGRM, KLBF, and TSPC. More firms are using short-term leverages more than long-term leverages. Market leverages are more widely used by the firm rather than total leverages. Long-term leverage and tangibility have significant positive correlation, this means that the firms with high asset tangibility have higher long-term leverage. Long-term leverage and size have strong positive correlation, this means that a larger firm has more long-term leverage than a small firm. Total leverage, short-term leverage, long-term leverage, and market leverage are negatively correlated with profitability. This means that firms with high profitability will have lower leverage. Profitability and tangibility have significant negative correlation. This indicates that the firm with low profit can use more leverage with one condition it has a high tangibility of 34

35 asset to secure the leverage. Tangibility and size have significant positive correlation, meaning that large firm should have high asset tang, so that it can use a high leverage. Growth and total leverage have significant positive correlation and the growth is negatively correlated with market leverage. This means that firms with higher growth use more total leverage than market leverage. Risk and growth have significant positive correlation, this means that firms with high growth have high risk. Profitability and risk have significant negative correlation, this means that firms with low profitability have low risk. The firms that have the highest profitability are UNVR, GGRM, INAF, KOMI, HMSP, and KAEF. The firms that have the lowest profitability are SMCB, ADMG, SULI, BRPT, FASW, and GJTL. The firms that have the highest size are ASII, INKP, TKIM, INTP, GGRM, and INDF. The firms that have the lowest size are RMBA, KOMI, DNKS, BUDI, KAEF, and INAF. The firms that have the highest tangibility are INTP, SMCB, INKP, FASW, ADMG, SMGR, and TKIM. The firms that have the lowest tangibility are RMBA, DNKS, TSPC, BRPT, INAF, and KLBF. The firms that have the highest growth are SULI, BRPT, CPIN, KLBF, ASII, HMSP, and INDF. The firms that have the lowest growth are INAF, KAEF, INDR, FASW, and INKP. The firms that have the highest risk are SMCB, HMSP, INAF, ADMG, AUTO, KOMI, and TSPC. The firms that have the lowest risk are SMGR, INKP, INDR, INDF, SULI, and TKIM. 35

36 3. LITERATURE REVIEW 3.1 Theories of Capital Structure One of the most insightful and important concerns in corporate finance is to determine how firms should finance their investments and operations. This is known as the capital structure problem. The study on the theory of capital structure endeavours to enlighten the use of the mix of securities. What the theory of capital structure concerns about should be the relative amounts of issued by firms of given securities, primary debt and equity. In Van Horne (1998), the theory of capital structure analysed the impact of the financing mix on the valuation of the firm. The theory also attempted to discover whether there existed an optimal capital structure for a firm. There are broadly two schools of thought. One school believes that the composition of the financing mix does not affect the cost of capital so that the capital structure has no relevance in the valuation of the firm. The proponents of the other school believe that the cost of capital is determined by the composition of the capital structure. The application of leverage results in a change in the cost of capital. They try to determine the optimal capital structure, at which level the overall cost of capital is minimal Modigliani-Miller Theory Modigliani and Miller suggest that the composition of the capital structure is an irrelevant factor in the company's market valuation. They have really attacked the traditional position that companies have the optimal capital structure. In Modigliani and Miller (1958) The Cost of Capital, Corporation Finance and the Theory of Investment, they have strengthened the net operating income approach by adding a behavioural dimension to it. They have been awarded the Nobel Prizes (Franco Modigliani in 1985, and Merton Miller in 1990) for their widely recognised contributions to financial theory. In Van Horne (1998), the Modigliani-Miller (MM) position is based on the following assumptions: (1) The fundamental building blocks for the hypothesis of MM is a perfect capital market. There is a free flow of information in the market that can easily be accessed by investors. There are no costs involved in obtaining the information. (2) Securities issued and traded in the market are infinitely divisible. (3) No transaction costs such as flotation costs, underpricing major issues, brokers, transfer taxes, etc.. (4) All participants in the market are rational that they are trying to maximise profits or minimise their losses. (5) All investors have homogeneous expectations about future earnings of all firms in the market. (6) The company can be classified into the class `equivalent return '. Firms in each class have the exact same profile of business risk. So the company can be taken as perfect substitutes for one another. All companies in a particular class have a common level of capitalisation rate. (7) There is no corporate tax. Modigliani and Miller (1958) have stated the arbitration process to support their position that the value of the company with leverage cannot be higher than the value of a company with no leverage. On the other hand, the value of a company with no leverage cannot be higher than the value of a company with leverage. The substance of this argument is that investors can replicate any combination of capital structure by substituting the company leverage with the `home-made ' leverage. Home-made leverage refers to individual loans prepared by investors in the equivalent ratio as the company with leverage. Therefore, leverage of company is not something that is distinctive that investors cannot carry out it alone. Therefore, the leverage in the capital structure 36

37 has no importance in a perfect capital market. It implies that, firms that are identical in all respects, except for their capital structure, must have the equal value. In the event that they have a different valuation, the arbitration process will initiate. This will maintain to occur until the two companies command the same valuations. At this position, the market reaches equilibrium or stability. A. Taxes and the Capital Structure The introduction of the tax element brings the complexity theory of capital structure. The assumption that there is no tax is relaxed to evaluate the validity of the hypothesis. Interests payable on debt are tax deductible substances, while retained earnings and dividends payable to equity do not enjoy the fiscal benefits. Therefore, every time the company employs debt in its capital structure, it gets a certain tax shield (Modigliani and Miller, 1963). Thus, the sum availables for sharing to the shareholders more in the case of a company with leverage than in a company with no leverage. However, utilisation of tax shields by the company is uncertain. A company's taxable income may fall or the company may experience losses in the future. In such a circumstance, companies do not have advantage of the tax shield available. Corporate tax rates can be reduced in the future, which will reach in a lower tax shield. This office can be liquidated, and the tax shield will not have any realisable value unlike any other asset. Alternatives such as leasing tax shelters, depreciation, investment allowances, etc., may be presented to the company, and will generate excessive tax shield (De Angelo and Masulis, 1980). Thus, the uncertainty associated with it can lead to decline in value of tax shields. The greater the uncertainty, the lower will be the value of tax shields. The presence of personal taxes can reduce the value of tax shields. This is because capital gains are normally taxed at a lower rate than regular income. In extreme cases the company retains all the profits, shareholders had no tax liability. Further, tax on capital gains is paid only if the security is sold. B. Merton Miller Hypothesis Merton Miller (1977) held that the capital structure decision is irrelevant even in the presence of corporate taxes and personal. Changes in capital structure had no impact on corporate valuation. This stands significantly different to the article Corporate Income Taxes and the Cost of Capital: A Correction jointly written by Modigliani and Miller (1963) in which they agreed debts have the advantage of substantial tax benefits. According to him, the influence of corporate taxes and personal taxes tend to get cancelled and the hypothesis of MM continues to apply even in the presence of taxes. Miller (1977) indicates that different investors have different rates of personal income tax. The tax-exempt investors prefer to invest in debt, while investors in tax brackets higher preferred equity investments. Miller (1977) argues that when the market is in a state of imbalance, the company will change their capital structure to confirm with the incidence of tax on investors. As companies increases the quantum of debt in their capital structure, debt supply in the market increases. This will deplete the capacity of 'clients' tax-free (investors) to absorb the debt. These companies would then sell their debt to investors in the next tax bracket. This process is continued to the stage where the company covers the investor classification in the same tax bracket income tax rates. Markets are required to be equilibrium when the personal tax rate investors are the same as the corporate income tax rate, at which point it is no longer potential for companies to improve the evaluation by changing the capital structure The Capital Structure Theory 37

38 The irrelevance capital structure theory by Modigliani and Miller (1958) was a milestone from which several related theories developed by relaxing the assumptions made by the study and adding new conditions of, among others, asymmetric information and agency costs (Leland and Pyle, 1977 ; Myers, 1984 ; La Porta, et al., 1996, 1997). Thus, by relaxing the assumptions of Modigliani and Miller (1958), capital structure is relevant to firm value. A. Pecking Order Theory According to this hypothesis, the company follows a specific order of preferences in financing decisions (Myers, 1984; Myers and Majluf, 1984). The most popular mode of financing is retained earnings. The advantage of financing through retained earnings is that it has no related flotation costs. Additionally, retained earnings do not require external supervision by the provider of capital. When the internal accruals are not adequate to finance the proposed investment, then the company resorts to debt financing. The issue of debt does not result in dilution of equity capital and has no implications on stock ownership. The next way of financing in the hierarchy is the issuance of preference capital. This was followed by a variety of hybrid instruments like convertible instruments. The least preferred mode of financing is issue of equity (Donaldson, 1961; Myers, 1984; Myers and Majluf, 1984). This is only reliable as a last option. Pecking order theory is a behavioural approach to capital structure. This is based on the principle that financing decisions are made in a way that causes the least difficulty to the management. B.3.1. Trade-off Theory The major benefit of debt financing is that it provides a tax shelter that increases the available remaining to be distributed to shareholders of equity. Nevertheless, the main disadvantage related with debt financing is the risk of bankruptcy (Warner, 1977; Haugen and Senbet, 1978, Andrade and Kaplan, 1998). Increased levels of leverage, while resulting in the availability of a larger tax shields also necessitate a higher cost line of financial distress. The company is trying to trade-off between the size of the tax shelter and financial distress costs. Higher probability of financial distress is in terms of start-ups and high growth businesses. The company is exposed to the risk of uncertain cash flow streams and low tangible asset base. Therefore, these type of companies should not place high confidence on the debt in their capital structure. On the other hand, firms with a stable revenue stream and sound asset base facing a lower risk of bankruptcy. This company can apply a moderately higher level of leverage in their capital structure. B.3.2. Bankruptcy Costs and the Capital Structure Various theories of capital structure is not attended to the existence of bankruptcy costs. In a perfect capital market, it is assumed that all company assets can be sold on their economic value without acquiring the costs of liquidation. Nevertheless, in actual situations, such as liquidation costs, legal fees and administration are significant (Warner, 1977; Haugen and Senbet, 1978, Andrade and Kaplan, 1998). Moreover, assets may be sold at distress prices below their economic value. Thus, its net realisable value is less than the economic value, which is a 'dead weight loss' to the system. The lenders will bear the cost of ex post bankruptcy, but they will continue the ex ante bankruptcy costs for firms in the form of high cost of debt. In the end, the shareholders bear the problem of ex ante bankruptcy costs and lower valuation due from the company. A company with leverage has a larger probability of bankruptcy than firms with no leverage. Hence, the cost of bankruptcy for firms with high leverage is higher. However, the cost of bankruptcy is not a linear function of leverage. When a company employs low levels of 38

39 leverage in capital structure, bankruptcy risk is not considerable. Thus, there is no influence of bankruptcy cost on corporate valuation, until the threshold is reached. Conversely, after a threshold level of leverage, bankruptcy becomes an existent threat. The possibility of bankruptcy significantly increases with further application of leverage. Bankruptcy costs rose at an increased rate beyond the stage of threshold. C.3.1. Asymmetric Information This hypothesis is based on the principle that the manager/person in having personal information about the characteristics of the flow back in a company or an investment opportunity. Thus capital structure is intended to reduce inefficiencies caused by asymmetric information. Stewart Myers and Nicholas Majluf (1984) in a pioneering article Corporate Financing and Investment Decisions When Firms have Information That Investors Do not Have argues that, if the investor is less well-informed than people in the company on company valuation, equity may be mispriced by the market. If the company is funding new projects by issuing equity, underpricing may be so strict that new investors capture more than the net present value (NPV) of the new project, which results in a net loss to existing shareholders. In this case, the project was rejected even though the NPV is positive (Myers, 1977). Underinvestment problems can be avoided if the company can finance investment by issuing securities that would have less or nil undervaluation. For instance, internal accruals do not have an element of undervaluation and in terms of the debt will be less severe undervaluation. Consequently, the firm uses equity financing only as a last choice. C.3.2. Signalling through Capital Structure Some theories suggest that changes in capital structure have information content about the valuation of the firm. These theories give explanations that capital structure changes are explicit signals about the firm s valuation, sent purposely by the management (Ross, 1977). An increase in the debt composition of the capital structure is commonly indicated as a signal of undervaluation of the firm. As the increased level of leverage is accompanied by a higher risk of bankruptcy, the increased level of debt implies the confidence of the management in the future prospects of the firm. Hence, it brings greater conviction than a simple announcement of undervalution of the firm by the management (Leland and Pyle, 1977; Myers and Majluf, 1984). On the other hand, an issue of equity is an indication that the firm is overvalued. The market interpretes that the management has decided to issue equity because it is valued higher than its intrinsic valued by the market. The markets normally respond favourably to moderate increases in leverage and negatively to new issue of equity (Ross, 1977). C.3.3. Agency Costs and the Capital Structure A significant amount of research during the last two decades has been dedicated to models in which capital structure is determined by agency costs, costs due to conflict of interest (Harris and Raviv, 1991). Firstly, conflicts of interest between shareholders and managers begin because managers are not allowed to 100% of the residual claims. Consequently the managers do not capture the entire gain from the profit enhancement activities, but they do accept the entire costs of these activities. The managers may hence put in less efforts in value enhancement activities and may also undertake to maximise their private gains by lavish perquisites, plush offices, empire building through sub-optimal investments, etc (Jensen, 1986). While the managers would have the entire costs of refraining from such inefficiencies, they are entitled to only a portion of the gains. The increase in the manager s stake in the firm decreases these inefficiencies. 39

40 Secondly, conflicts also come up between the interests of debt holders and equity holders (Jensen and Meckling, 1976). If an investment financed with debt yields high returns (higher than the cost of debt), equity holders are allowed to the gains. On the other hand, if the investment fails, the debt holders experience the losses due to limited liability of the equity holders. As a consequence, equity holders may gain from investing in very risky projects even if they are value decreasing. Such investments result in a decline in the value of debt. The loss in the value of equity from regrettable investments can be more than compensated by the gains in equity value at the cost of the lenders. The lenders to the firm protect themselves against expropriation by impressive certain conditions on the firm. These circumstances are called as protective covenants and stay in strong point till the debt is repaid. These conditions may relate to limitations on further borrowings by the firm, cap on payment of dividends, managerial payment, sale of assets, limitations on new investment, etc. These conditions may guide to sub-optimal operations resulting in inefficiencies. Additionally, the lenders put in place tough monitoring and corrective mechanisms to implement the debt covenants. The monitoring and enforcement costs are approved on to the firms in the kind of higher cost of debt. These expenses together with the cost of inefficiencies (due to the covenants) are called agency costs (Jensen and Meckling, 1976). As residual owners, the shareholders have an incentive to make sure that agency costs are minimised. The existence of agency costs work as a disincentive to the issuance of debt. The agency cost may be practically non-existent at low levels of leverage. Nevertheless, after the entry point, the lenders initiate perceiving the firm to be increasingly risky. This may result in an unequal increase in the agency costs due to the necessitate for widespread monitoring The Conclusions What Variables We Use for Our Research, and Why These, Theories Predictions of the Relationship between Variables, and Some Previous Research Findings The following sub-sections imply the conclusions what variables we use for our research and the reasons, theories predictions of the relationship between variables, and some previous research findings Selected Variables regarding Capital Structure for Research Question 1a, 1b, 1c, 1d, and 1e After reviewing the pecking order theory and trade-off theory, we test the theories by using selected variables. As our research question that stated in chapter 1, what are the determinants of capital structure of the firms in the manufacturing sector in Indonesia? Hence, our minor research questions are as follows: as implied by the trade-off theory and the pecking order theory, do growth opportunities have positive relationship with debt ratio?; As the pecking order hypothesis, does firm s profitability has a negative relationship with level of debt? And as implied by the trade-off theory, does firm s profitability has a positive relationship with debt ratio?; In accordance with the pecking order theory and trade-off theory, is there a negative relationship between risk (earnings volatility) and debt ratio?; As suggested by the trade-off theory, does size has a positive relationship with debt ratio? And as suggested by the pecking order theory of the capital structure, is there a negative relationship between level of debt and size of the firm?; In accordance with the trade-off theory, is there a positive relationship between asset tangibility and level of debt? Therefore, the relevant variables we used are: debt ratios as the dependent variable, and the growth opportunities, profitability, risk, size, asset tangibility as the independent variables. The selection of independent variables is also conducted by previous empirical studies such as Pandey (2001), Sogorb-Mira and López-Gracia (2003), and Huang and Song (2002). 40

41 The test of determinants of capital structure of the firms in the manufacturing sector in Indonesia is important as these firms have different characteristics. We test it based on pecking order theory and trade-off theory. We choose four debt ratios in this study, they are total leverage, short-term leverage, long-term leverage, and market leverage. These measures of debt ratios examine the capital employed and thus, best represent the effects of past financing decisions. We chose tangibility of assets, as the tangibility of assets represents the effect of the collateral value of assets of the firm s gearing level. There are various conceptions for the effect of tangibility on leverage decisions. If debt can be secured against assets, the borrower is restricted to using debt funds for specific projects. Creditors have an improved guarantee of repayment, but without collateralised assets, such a guarantee does not exist. Firm size provides a measure of the agency costs of equity and the demand for risk sharing. Firm size is likely to capture other firm characteristics as well (e.g., their reputation in debt markets or the extent their assets are diversified). For growth opportunities, the trade-off theory suggests that firms with more investment opportunities have less leverage because they have stronger incentives to avoid under-investment and asset substitution that can arise from stockholder-bondholder agency conflicts. Jensen s (1986) free cash flow theory similarly discusses that firms with more investment opportunities have less need for the disciplining effect of debt payments to control free cash flows. Meanwhile, profitability plays an important role in leverage decisions. Profitability is proxied by return on assets. ROA represents the contribution of the firm s assets on profitability creation. Profitability is a measure of earning power of a firm. The earning power of a firm is generally the basic concern of its shareholders. Finally, we choose earnings volatility as it measures the variability of the firm's cash flows as a proxy for the costs of monitoring managers and of the risk of an insider's position. The use of longer time periods causes a significant loss of the sample size. The following is the theories prediction of the relationship between variables and some previous research findings. Growth Opportunities According to pecking order theory hypothesis, a firm will use first internally generated funds which may not be sufficient for a growing firm. And the next option for the growing firms is to use debt financing which implies that a growing firm will have a high leverage (Drobetz and Fix 2003). Applying pecking order arguments, growing firms place a greater demand on the internally generated funds of the firm. Consequently, firms with relatively high growth will tend to issue less security subject to information asymmetries, i.e. short-term debt. This should lead to firms with relatively higher growth having more leverage. The same relationship is supported by trade-off theory, too. According to this theory, growth causes firms to shift financing from new equity to debt, as they need more funds to reduce the agency problem. Following trade-off theory, for companies with growth opportunities, the use of debt is limited as in the case of bankruptcy, the value of growth opportunities will be close to zero, growth opportunities are a particular case of intangible assets (Myers, 1984; Williamson, 1988 and Harris and Raviv, 1990). Firms with less growth prospects should use debt because it has a disciplinary role (Jensen, 1986; Stulz, 1990). Firms with growth opportunities may invest suboptimally, and therefore creditors will be more reluctant to lend for long horizons. This problem 41

42 can be solved by short-term financing (Titman and Wessels, 1988) or by convertible bonds (Jensen and Meckling, 1976; Smith and Warner, 1979). According to trade-off theory, the retained earnings of high growth firms increase and they issue more debt to maintain the target debt ratio. Thus, positive relationship between debt ratio and growth is expected based on this argument. The signalling hypothesis is based on the impact of information asymmetries on debt policies. Firms with higher growth opportunities face greater information disparities and therefore are expected to have higher debt levels to signal higher quality (Gul, 1999). According to agency costs, on the other hand, Myers (1977) argued that, due to agency problems, firms investing in assets that might generate high growth opportunities in the future, faced difficulties in borrowing against such assets. For this reason, we may now instead expect a negative relationship between growth and leverage. Previous research findings have different conclusion. For example, Huang and Song (2002) argued that sales growth rate was the past growth experience, while Tobin s Q better proxied future growth opportunities, although sales growth rate as well as Tobin s Q (market-tobook ratio of total assets) were employed to measure growth opportunities in this study. Jung, Kim and Stulz (1996) showed, if management pursued growth objectives, management and shareholder interests tended to coincide for firms with strong investment opportunities. But for firms lacking investment opportunities, debt served to limit the agency costs of managerial discretion as suggested by Jensen (1986) and Stulz (1990). The findings of Berger, Ofek, and Yermack (1997) also confirmed the disciplinary role of debt. The findings of Kim and Sorensen (1986), Smith and Watts (1992), Wald (1999), Rajan and Zingales (1955), and Booth et al. (2001) suggested growth opportunities were negatively related with leverage. Titman and Wessels (1988) found a negative relationship. Myers (1977) argued that high-growth firms might hold more real options for future investment than low-growth firms. If high-growth firms need extra equity financing to exercise such options in the future, a firm with outstanding debt may forgo this opportunity because such an investment effectively transfers wealth from stockholders to debt holders. So firms with high growth opportunity may not issue debt in the first place and leverage is expected to be negatively related with growth opportunities. Jensen and Meckling (1976) also suggested that leverage increased with lack of growth opportunities. However, Kester (1986), Rajan and Zingales (1995) reported a positive relationship between leverage and growth. Huang and Song found that firms experienced a high growth rate in the past tend to have higher leverage, while firms that had a good growth opportunity in the future (a higher Tobin s Q) tend to have lower leverage. Profitability The pecking order theory, based on works by Myers and Majluf (1984) suggests that firms have a pecking-order in the choice of financing their activities. Roughly, this theory states that firms prefer internal funds rather than external funds. If external finance is required, the first choice is to issue debt, then possibly with hybrid securities such as convertible bonds, then eventually equity as a last resort (Brealey and Myers, 1991). This behaviour may be due to the costs of issuing new equity, as a result of asymmetric information or transaction costs. 42

43 All things being equal, the more profitable the firms are, the more internal financing they will have, and therefore we should expect a negative relationship between leverage and profitability. This relationship is one of the most systematic findings in the empirical literature (Harris and Raviv, 1991; Rajan and Zingales, 1995; Booth et al., 2001). There are conflicting theoretical predictions on the effects of profitability on leverage (Rajan and Zingales, 1995); while Myers and Majluf (1984) predicted a negative relationship according to the pecking order theory, Jensen (1986) predicted a positive relationship. Following the pecking order theory, profitable firms, which have access to retained profits, can use these for firm financing rather than accessing outside sources. In the pecking order model, higher earnings should result in less book leverage. Firms prefer raising capital, first from retained earnings, second from debt, and third from issuing new equity. This behaviour is due to the costs associated with new equity issues in the presence of information asymmetries. Debt typically grows when investment exceeds retained earnings and fall when investment is less than retained earnings. Accordingly, the pecking order model predicts a negative relationship between book leverage and profitability. The pecking order theory predicts that firms with a lot of profits and few investments have little debt. Since the market value increases with profitability, the negative relationship between book leverage and profitability also holds for market leverage. However, in a trade-off theory framework, an opposite conclusion is expected. When firms are profitable, they should prefer debt to benefit from the tax shield. In addition, if past profitability is a good proxy for future profitability, profitable firms can borrow more as the likelihood of paying back the loans is greater. From the trade-off theory point of view more profitable firms are exposed to lower risks of bankruptcy and have greater incentive to employ debt to exploit interest tax shields. According to the trade-off theory, agency costs, taxes, and bankruptcy costs push more profitable firms toward higher book leverage. First, expected bankruptcy costs decline when profitability increases. Second, the deductability of corporate interest payments induces more profitable firms to finance with debt. Finally, in the agency models of Jensen and Meckling (1976), Easterbrook (1984), and Jensen (1986), higher leverage helps to control agency problems by forcing managers to pay out more of the firm s excess cash. The trade-off theory predicts that leverage increases with profitability. Since the market value also increases with profitability, this positive relation does not necessarily apply for market leverage. The strong commitment to pay out a larger fraction of their pre-interest earnings to debt payments suggests a positive relationship between book leverage and profitability. This notion is also consistent with the signalling hypothesis by Ross (1977), where higher levels of debt can be used by managers to signal an optimistic future for the firm. Meanwhile, based on agency theory, there are two possible explanations. Jensen (1986) predicted a positive relationship, if the market for corporate control was effective. However, if it was ineffective, He predicted a negative relationship between profitability and leverage, and a positive relationship between profitability and financial leverage if the market for corporate control was effective because debt reduced the free cash flow generated by profitability. Much theoretical work has been done since Modigliani and Miller (1958), no consistent predictions have been reached of the relationship between profitability and leverage. Myers (1977) stated that firms preferred raising capital from retained earnings rather than from debt or from issuing equity. This is the so-called pecking order theory. If pecking order holds true, then, higher profitability will correspond to lower debt-equity ratio. Myers (1984) pecking order theory of capital structure showed that if a firm was profitable then it would be more likely that financing 43

44 came from internal sources rather than external sources. More profitable firms were expected to hold less debt, since it was easier and more cost effective to finance internally. In contrast to theoretical studies, most empirical studies showed that leverage was negatively related to profitability. Friend and Lang (1988), and Titman and Wessels (1988) obtained such findings from US firms. Kester (1986) found that leverage was negatively related to profitability in both the US and Japan. More recent studies using international data also confirmed this finding (Rajan and Zingales (1995), and Wald (1999) for developed countries, Wiwattanakantang (1999) and Booth et al. (2001) for developing countries. Long and Maltiz (1985) found leverage to be positively related to profitability, but the relationship was not statistically significant. Wald (1999) even claimed that profitability has the largest single effect on debt/asset ratios. Huang and Song (2002) found that profitability was strongly negatively related with total leverage. Chang (1999) showed that the optimal contract between the corporate insider and outside investors could be interpreted as a combination of debt and equity, and profitable firms tended to use less debt. Meanwhile, Jensen, Solberg and Zorn (1992) found a positive one (supporting the trade-off theory). Risk According to pecking order theory and tradeoff theory, earning volatility is considered to be either the inherent business risk in the operations of a firm or a result of inefficient management practices. In either case earning volatility is proxy for the probability of financial distress and the firm will have to pay risk premium to outside fund providers. To reduce the cost of capital, a firm will first use internally generated funds and then outsider funds. This suggests that earning volatility is negatively related with leverage. This is the combined prediction of trade-off theory and pecking order theory. According to pecking order theory and tradeoff theory, income variability is a measure of business risk. Since higher variability in earnings indicates that the probability of bankruptcy increases, we can expect that firms with higher income variability have lower leverage. Therefore, the trade-off model allows the same prediction, but the reasoning is slightly different. More volatile cash flows increase the probability of default, implying a negative relationship between leverage and volatility of cash flows. As expected, the relationship between leverage and volatility is negative. This supports both the trade-off theory (more volatile cash flows increase the probability of default) and the pecking order theory (issuing equity is more costly for firms with volatile cash flows). Cools (1993) said that agency theory suggested positive relationship between earning volatility and leverage. He said that the problem of underinvestment decreased when the volatility of firm returns increased. Booth et al., (2001), Bradley et. al., (1984), Chaplinsky and Niehaus, (1993), Wald, (1999), and Titman and Wessels (1988), all these studies found that business risk was negatively correlated with leverage. Huang and Song (2002) found that the positive relation between total liabilities ratio and volatility was consistent with Hsia s (1981) view that firms with higher leverage level tended to make riskier investment. Size According to tradeoff theory, first, large firms don t consider the direct bankruptcy costs as an active variable in deciding the level of leverage as these costs are fixed by constitution and constitute a smaller proportion of the total firm s value. And also, larger firms being more diversified have lesser chances of bankruptcy (Titman and Wessels 1988). Following this, one 44

45 may expect a positive relationship between size and leverage of a firm. The trade-off theory predicts an inverse relationship between size and the probability of bankruptcy. Hence, there is a positive relationship between size and leverage. Second, contrary to first view, Rajan and Zingales (1995) argued that there was less asymmetrical information about the larger firms. This reduced the chances of undervaluation of the new equity issue and thus encouraged the large firms to use equity financing. This means that there is negative relationship between size and leverage of a firm. Following Rajan and Zingales (1995), we expect a negative relationship between size and leverage of the firm. Therefore, the pecking order theory of the capital structure predicts a negative relationship between leverage and size, as larger firms exhibiting increasing preference for equity relative to debt. Meanwhile, previous research also has different results. Titman and Wessels (1988) and Drobetz and Fix (2003) measure of size was the natural logarithm of net sales. However, they stated that net sales was a better proxy for size, because many firms attempted to keep their reported size of asset as small as possible, e.g., by using lease contracts. Size can be regarded as a proxy for information asymmetry between firm insiders and the capital markets. Large firms are more closely observed by analysts and should therefore be more capable of issuing informationally more sensitive equity, and have lower debt. Akhtar and Oliver (2006) found that more profitable firms had significantly less leverage regardless of whether they were MNCs or DCs. This supports the pecking-order theory of capital structure for both MNCs and DCs. Rajan and Zingales (1995) and Wald (1999) found that larger firms in Germany tended to have less debt. Meanwhile, many studies suggest there is a positive relation between leverage and size. Drobetz and Fix (2003) said that size was positively related to leverage, indicating that size was a proxy for a low probability of default. Empirical studies, such as Marsh (1982), Rajan and Zingales (1995), Wald (1999), and Booth et al. (2001), generally found that leverage was positively correlated with company size. Huang and Song found that size was positively related with total liability. Marsh (1982) found that large firms more often chosen long-term debt while small firms chosen short-term debt. Large firms may be able to take advantage of economies of scale in issuing long-term debt, and may even have bargaining power over creditors. So the cost of issuing debt and equity is negatively related to firm size. However, size may also be a proxy for the information that outside investors have. Fama and Jensen (1983) argued that larger firms tended to provide more information to lenders than smaller ones. Rajan and Zingales (1995) argued that larger firms tended to disclose more information to outside investors than smaller ones. Overall, larger firms with less asymmetric information problems should tend to have more equity than debt and thus have lower leverage. However, larger firms are often more diversified and have more stable cash flow; the probability of bankruptcy for large firms is smaller compared with smaller ones, ceteris paribus. Both arguments suggest size should be positively related with leverage. According to Whited (1992) small firms could not access long-term debt markets since their growth opportunities exceeded their collateralizable assets. Titman and Wessels (1988) argued that larger firms had easier access to capital markets. Tangibility From a pecking order theory perspective, firms with few tangible assets are more sensitive to informational asymmetries. These firms will thus issue debt rather than equity when 45

46 they need external financing (Harris and Raviv, 1991), leading to an expected negative relation between the importance of intangible assets and leverage. According to trade-off hypothesis, tangible assets act as collateral and provide security to lenders in the event of financial distress. Hence, the tradeoff theory predicts a positive relationship between measures of leverage and the proportion of tangible assets. On the relationship between tangibility and capital structure, theories generally state that tangibility is positively related to leverage. Tangibility is almost always positively correlated with leverage. This supports the prediction of the trade-off theory that the debt-capacity increases with the proportion of tangible assets on the balance sheet. Based on the agency problems between managers and shareholders, Harris and Raviv (1990) suggested that firms with more tangible assets should take more debt. This is due to the behaviour of managers who refuse to liquidate the firm even when the liquidation value is higher than the value of the firm as a going concern. Indeed, by increasing the leverage, the probability of default will increase which is to the benefit of the shareholders. In an agency theory framework, debt can have another disciplinary role: by increasing the debt level, the free cash flow will decrease (Grossman and Hart, 1982; Jensen, 1986; Stulz, 1990). As opposed to the former, this disciplinary role of debt should mainly occur in firms with few tangible assets, because in such a case it is very difficult to monitor the excessive expenses of managers. Harris and Raviv (1990) predicted that firm with higher liquidation value would have more debt. Firms with more tangible assets usually have a higher liquidation value although we are aware that assets specificity may play a role and result in some distortion. In general, firms with a higher proportion of tangible assets are more likely to be in a mature industry thus less risky, which affords higher financial leverage. In Drobetz and Fix (2003), previous empirical studies by Titman and Wessels (1988), Rajan and Zingales (1995) and Fama and French (2000) argued that the ratio of fixed to total assets (tangibility) should be an important factor for leverage. The tangibility of assets represents the effect of the collateral value of assets of the firm s gearing level. Huang and Song (2002) found that debt ratio was positively correlated with tangibility, the change of total liabilities ratio was significantly positively correlated with the change of tangibility. Empirical studies that confirm the above theoretical prediction include Marsh (1982), Long and Malitz (1985), Friend and Lang (1988), Rajan and Zingales (1995), and Wald (1999). As the non-debt portion of liabilities does not need collateral, tangibility is expected to affect the longterm debt or total debt ratio rather than total liabilities ratio Selected Variables for Research Question 2 Accordingly, after reviewing the pecking order theory, we test the second research question: how do firms in the manufacturing sector in Indonesia raise capital for investments, internally or externally (with debt, equity, or debt to repurchase equity). Hence, the relevant variables we used are as follow: financial deficit as independent variable and net debt issue, net equity issue, and net debt issue to repurchase equity as dependent variables. 46

47 Why do we test hypothesis 2 in this research is that, how do firms in the manufacturing sector in LQ45 index financing the firms deficit as these firms are experiencing financial deficit over the period of time (see table). We chose net debt issue, net equity issue, and net debt issue to repurchase equity as dependent variables as pecking order theory suggests firms to prefer internal financing to external financing, and prefer debt to equity. The following is the theories prediction of the relationship between variables and some previous research findings. The theories prediction is as follows. Based on asymmetric information, the underinvestment problem can be avoided if the firm can finance the investment by issuing securities that will have lesser or nil undervaluation. For example, internal accruals do not have any element of undervaluation and in case of debt the undervaluation will be less severe. Therefore, firms use equity financing only as a last resort. Pecking order theory states that changes in debt have played an important role in assessing the pecking order theory. This is because the financing deficit is supposed to drive debt according to this theory. Shyam-Sunder and Myers (1994, 1999) paper tested traditional capital structure models against the alternative of a pecking order model of corporate financing. The basic pecking order model, which predicts external debt financing driven by the internal financial deficit, has much greater explanatory power than a static trade-off model which predicts that each firm adjusts toward an optimal debt ratio. Shyam-Sunder and Myers (1994) summarized main conclusions regarding pot as follows. (1) The pecking order is an effective first-order descriptor of corporate financing behaviour. (2) The co-efficient and significance of the pecking order variable change hardly at all. (3) The strong performance of the pecking order does not occur just because firms fund unanticipated cash needs with debt in the short run. Shyam-Sunder and Myers (1999) summarized the main conclusions regarding pot as follows. (1) The pecking order is an excellent first-order descriptor of corporate financing behaviour, for their sample of mature corporations. (2) The strong performance of the pecking order does not occur just because firms fund unanticipated cash needs with debt in the short run. Their (1994, 1999) results suggested that firms planned to finance anticipated deficits with debt. Previous research from Indonesia, Ari Christianti (2008), concluded that: (1) The results of this study does not fully support the pecking order theory in explaining the behaviour of firm financing in the IDX especially the manufacturing sector. This can be explained from the results of the estimation that shows a negative and significant co-efficient of pecking order theory. (2) It may be explained from the results of this study is the Indonesian capital market conditions that are different from capital markets in developed countries studied by Shyam-Sunder and Myers (1999), Frank and Goyal (2003) and Jong, Verbeek, and Verwijmeren (2005). In addition, the impact of economic crisis in 1997 still affected the economic condition of Indonesia until Cotei and Farhat (2008) investigated the models used in testing the trade-off and pecking order theories at the industry level as well as across all industries. Under the pecking order model, firms in financing deficit used debt to finance their new investment whereas firms in financing surplus ended up retiring debt rather than repurchasing equity. Hence, their results showed that for the pecking order model, they rejected the hypothesis that firms had a symmetric behaviour regardless of the sign of the financing variable. Their results showed that firms had the tendency to 47

48 reduce debt by a significantly higher proportion when they had financing surplus compared to the proportion of debt issued when they had financing deficit. Joher, Ahmed, and Hisham (2009) paper draw on studies from finance and accounting literature to revisit pecking order and static trade-off-hypothesis in the context of Malaysia capital market. Their evidence from pecking order model suggested that the internal fund deficiency was the most important determinant that possibly explained the issuance of new debt. Hence pecking order hypothesis is well explained in Malaysian capital market despite the lower predicting power. The expanded pecking order model provides more vibrant explanation for debt issuance with higher predictive power. Meanwhile, their result for static trade-off-model was not fit to explain the issuance of new debt issue in Malaysian capital market. This is an interesting findings that confirm the fact that Malaysian firms do not too much care about tax-shield benefit derive from employ both debt and non-debt tax-shield Selected Variables for Research Question 3a, 3b, and 3c After reviewing pecking order theory, trade-off theory, signalling theory, and asymmetric information, we test the third research questions: if debt is a policy matter, what will happen to the firm s stock price if firms issue new debt, new equity, or issue debt to repurchase equity. Therefore, the relevant variables we examined are the firm s stock price as dependent variable, and as independent variables are net debt issue, net equity issue, and net debt issue to repurchase equity. The test of hypothesis 3 is important to conduct as empirical evidence on the effect of capital structure choice on stock market reaction is limited. Hence, we examine the relationship between capital structure and stock price based on pecking order theory, trade-off theory, signalling theory, and asymmetric information. When a firm issues, repurchases or exchanges one security for another, it changes its capital structure and will give influence on stock market reaction. The following is the theories prediction of the relationship between variables and some previous research findings. Based on signalling through capital structure, the increased level of leverage is accompanied by a higher risk of bankruptcy, the increased level of debt indicates the confidence of the management in the future prospects of the firm. Hence, it carries greater conviction than a mere announcement of undervaluation of the firm, by the management. On the other hand, an issue of equity is a signal that the firm is overvalued. The market concludes that the management has decided to offer equity because it is valued higher than its intrinsic worth by the market. The markets normally react favourably to moderate increases in leverage and negatively to fresh issue of equity. Under the trade-off theory, firms will only take actions if they expect benefits. An implication of the theory is that the market reaction to both equity and debt securities will be positive. The market response to a leverage change confounds two pieces of information: the revelation of the fact that the firm s conditions have changed, necessitating financing, and the effect of the financing on security valuations. The information included in security issuance decisions could be either good news or bad news. It is good news if the firm issues securities to take advantage of a promising new opportunity that has not previously anticipated. It might be bad news if the firm issues securities because the firm actually needs more resources than anticipated to conduct operations. A firm may also issues securities now in anticipation of a change in future needs. This implies that the trade-off theory by itself places no obvious restrictions on the market valuation effects of issuing decisions. Everything depends on the setting. 48

49 Jung et al. (1996) suggested an agency perspective and argued that equity issues by firms with poor growth prospects reflected agency problems between managers and shareholders. If this is the case, then stock prices will react negatively to the news of equity issues. The pecking order theory is usually interpreted as predicting that securities with more adverse selection (equity) will result in more negative market reaction. Securities with less adverse selection (debt) will result in less negative or no market reaction. This is of course, still rest on some assumptions about market anticipations. Meanwhile, literature offers multiple explanations for buybacks. Some of these explanations have theoretical backgrounds and some are formed from empirical studies. The following theory is explaining our hypotheses. Based on the undervaluation hypothesis, stock repurchases offer flexibility not only for distributing the excess of funds but also the timing of distributing these funds. This flexibility in timing is beneficial because firms can wait to repurchase until the stock price is undervalued. The undervaluation hypothesis is based on the premise that information asymmetry between insiders and shareholders may cause a firm to be misvalued. If insiders believe that the stock is undervalued, the firm may repurchase stock as a signal to the market or to invest in its own stock and acquire mispriced shares. According to this hypothesis, the market interprets the action as an indication that the stock is undervalued (Amy K. Dittmar (1999). Because of the asymmetric information between managers and shareholders, share repurchase announcements are considered to reveal private information that managers have about the value of the company (in Smura). The information/signalling hypothesis has three immediate implications: repurchase announcements should be accompanied by positive price changes; repurchase announcements should be followed (though not necessarily immediately) by positive news about profitability or cash flows; and repurchase announcements should be immediately followed by positive changes in the market s expectation about future profitability (in Gustavo Grullon and Roni Michaely, 2002). Some previous empirical evidence regarding to debt issue on stock price are the following. Announcements of ordinary debt issues generate zero market reaction on average (see Eckbo (1986) and Antweiler and Frank (2006)). The zero market reaction to corporate debt issues is robust to various attempts to control for partial anticipation. Ross (1977) showed that good corporate performance could give a signal with a high portion of debt in their capital structure. Ross (1977) assumed the firms that are less well performaning would not use debt in large portion as it would be followed by the high chance of bankruptcy. By using these assumptions in which the company will use the good performance of higher debt, while firms that are less well performaning will use more of equity. Ross (1977) assumed that investors would be able to distinguish the company's performance by looking at the company's capital structure and they would give a higher value on the company with larger debt portion. It indicated that the result did not support the stated signalling theory. The result indicated that the greater the leverage, the greater the possibility of financial distress leading to bankruptcy. When the company went bankrupt, shareholders would lose money they have invested in the company (Peirson et al, 2002). Exchange of common for debt/preferred stock generates positive stock price reactions while exchange of debt/preferred for common stock generates negative reactions (Masulis, 1980a). 49

50 Summarizing the event study evidence, Eckbo and Masulis (1995) concluded that announcements of security issues typically generated a non-positive stock price reaction. In Indonesia, the regression coefficient between leverage and stock price is significantly negative. The use of high leverage will be responded by the market with a fall in stock prices. The results are consistent with the findings of a negative relationship between leverage and stock price as proposed by Frank and Goyal (2003). Relationship between the two variables will be positive at the time the company has many tangible assets that will secure leverage of companies. Announcements of convertible debt issues result in mildly negative stock price reactions (Dann and Mikkelson, 1984 ; and Mikkelson and Partch, 1986). The valuation effects are the most negative for common stock issues, slightly less negative for convertible debt issues and least negative (zero) for straight debt issues. The effects are more negative the larger the issue. Some previous empirical evidence regarding the equity issue on stock price are the following. Announcements of equity issues result in significant negative stock price reactions (Asquith and Mullins Jr., 1986; Masulis and Korwar, 1986; and Antweiler and Frank, 2006). The negative market reaction to equity issues and zero market reaction to debt issues is consistent with adverse selection arguments. Indeed, there are other interpretations. Jung et al. (1996) showed that firms without valuable investment opportunities experienced a more negative stock price reaction to equity issues than did firms with better investment opportunities. Thus, agency cost arguments could also explain the existing evidence on security issues. Further support for the agency view came from the finding that firms without valuable investment opportunities issuing equity invest more than similar firms issuing debt and that firms with low managerial ownership have worse stock price reaction to new equity issue announcements than firms with high managerial ownership do. The impact of equity issues appears to differ between countries. Several studies find positive market reaction to equity issues around the world (Eckbo et al., 2007) for a summary). To understand this evidence, Eckbo and Masulis (1992) and more recently Eckbo and Norli (2004) examine stock price reactions to equity issues conditional on a firm s choice of flotation method. Firms can issue equity using uninsured rights, standby rights, firm commitment underwriting and private placements. The stock price reactions to equity issues depend on the floatation method. For U.S. firms Eckbo and Masulis (1992) found that the average announcement-period abnormal returns were insignificant for uninsured rights offerings and they were significantly negative for firm-commitment underwritten offerings. Eckbo and Norli (2004) studied equity issuances on the Oslo Stock Exchange. They found that uninsured rights offerings and private placements resulted in positive stock price reactions while standby rights offerings generated negative market reactions. These papers interpreted the effect of the flotation method as reflecting different degrees of adverse selection problems. Some previous empirical evidence regarding the stock repurchases on stock price are as follows. Many studies show that repurchases are associated with a positive stock price reaction. Vermaelen (1981), Dann (1981), and Comment and Jarell (1991) found the positive stock price reaction at the announcement of a stock repurchase program should correct the misevaluation. Ikenberry, Lakonishok and Vermaelen (1995) showed that this increase might not be sufficient to correct the price since repurchasing firms, particularly low market to book firms, earned a positive abnormal return during the four years subsequent to the announcement. The amount of information available and the accuracy of the valuation of firms by the market could affect firms repurchase decisions. 50

51 According to Jensen (1986), firms repurchased stock to distribute excess cash flow. Stephens and Weisbach (1998) supported this hypothesis, as they found a positive relation between repurchases and levels of cash flow. Stephens and Weisbach also showed that repurchase activity was negatively correlated with prior stock returns, indicating that firms repurchased stock when their stock prices were perceived as undervalued. This result agrees with Vermaelen s (1981) findings that firms repurchase stock to signal undervaluation. Thus, firms repurchase stock when they are undervalued and have the excess cash to distribute. Masulis (1980b), Dann (1981), and Antweiler and Frank (2006) also found that the announcement effects were positive when common stock is repurchased. According to Brav et al. (2005.b.) discovered on their survey that only 22.5 percent of executives believed that reducing repurchases had negative consequences. On the other hand, almost 90 percent thought that reducing dividends had negative consequences Selected Variables for Research Question 4 Accordingly, after reviewing the pecking order theory, we test the theories by raising the following research question: in the context of firm s life cycle, do younger and growth firms follow the pecking order more closely. The objective of testing hypothesis 4 is to examine, in the context of firm s life cycle, whether younger and growth firms follow the pecking order more closely as implied by the pecking order theory of financing proposed by Myers (1984) and Myers and Maljuf (1984). It is important to examine the firm s capital structure over the life cycle of the firm in solving the problem of the firm s financing deficit. Firms in different life cycle stages have different characteristics especially regarding information asymmetry. Mature firms have less information asymmetry whereas growth firms have more information asymmetry. Firms with less information asymmetry are suggested to choose equity, while firms with more information asymmetry are suggested to retain earning as their capital structure. Therefore, the relevant variables are newly retained earnings, net debt issued, and net equity issued as dependent variables, and for the independent variable is financing deficit. We test hypothesis 4 to examine which firm s life cycle follow the pecking order more closely. It is the most interesting part of this research as firm life cycle has different capital structure choices as implied by pecking order theory. The following is the theories prediction of the relationship between variables and some previous research findings. As implied by the pecking order theory of financing of Myers (1984) and Myers and Maljuf (1984), the theory was based on asymmetric information between investors and firm managers. Due to the valuation discount that less-informed investors apply to newly issued securities, firms resort to internal funds first, then debt and equity last to satisfy their financing needs. In the context of a firm s life cycle, we expect that asymmetric information problems are more severe among young, growth firms compared to firms that have reached maturity. Older and more mature firms are more closely followed by analysts and are better known to investors, and should suffer less from problems of information asymmetry. Hence, the theory predicts that younger, fast-growing firms should be following the pecking order more closely. The theory s prediction that firms with the greatest information asymmetry problems (specifically young growth firms) are especially those that should be making financing choices based on the pecking order. 51

52 The trade-off theory stated that debt created a tax shield advantage through interest payments (DeAngelo and Masulis, 1980), which was balanced by the cost of bankruptcy (Baxter, 1967; Stiglitz, 1972; Kraus and Litzenberger, 1973; and Kim, 1978) to reach the optimal capital structure. According to the theory, the retained earnings of high growth firms increased and they issued more debt to maintain the target debt ratio. Thus, positive relationship between debt ratio and growth was expected based on this argument. However, according to the agency theory of Jensen and Meckling's (1976) and Jensen's (1986), the issuance of debt by low growth firms provides a device for monitoring and controlling managers by determining the market reaction to debt issuance by firm's with different growth rates. Therefore, following JM's and Jensen's arguments, low growth firms should increase debt levels in their capital structure. Many previous research of capital structure of the firms have been studied over life cycle stages in the context of the pecking order theory, trade-off theory (presence taxes and bankruptcy costs), and agency cost theory. The empirical evidence for the pecking order theory has been mixed. Shyam-Sunder and Myers (1999) proposed a direct test of the pecking order and found strong support for the theory among a sample of large firms. Myers (1977) argued that firms with high growth opportunity might not issue debt in the first place and leverage was expected to be negatively related with growth opportunities. Frank and Goyal (2003) found that large firms fitted the pecking order theory better than of small firms. Bulan and Yan (2007) findings showed that older, more stable and highly profitable firms with few growth opportunities and good credit histories were more suited to use internal funds first, and then debt before equity for their financing needs. Overall, they found that the pecking order theory described the financing patterns of mature firms better than of growth firms. This is contrary to the theory s prediction that firms with the greatest information asymmetry problems (specifically young, growth firms) are precisely those that should be making financing choices according to the pecking order. Overall, Bulan and Yan (2007) found that the pecking order theory described the financing patterns of mature firms better than that of younger growth firms. Bulan and Yan (2009) examined the central prediction of the pecking order theory of financing among firms in two distinct life cycle stages, namely growth and maturity. They found that within a life cycle stage, where levels of debt capacity and external financing needs were more homogeneous, and after sufficiently controlling for debt capacity constraints, firms with high adverse selection costs followed the pecking order more closely, consistent with the theory. Diamond (1989) showed that mature firms had a good reputation so that they were able to obtain better loan rates compared to their younger firm counterparts. Helwege and Liang (1996) followed a sample of recent IPO firms and found that these firms decisions to access the external finance markets as well as their choice of type of external finance was inconsistent with the pecking order. Petersen and Rajan (1995) presented evidence that older and more mature firms had access to a lower cost of debt, all else equal. Furthermore, mature firms generally have more internal funds due to higher profitability and lower growth opportunities. Hence, by nature of their life cycle stage, they concluded that mature firms were in a better position to following the pecking order. Hatfield, Cheng, and Davidson (1994), stated that, one might expect that a high growth firm could afford to have greater financial leverage because it could generate enough earnings to 52

53 support the additional interest expense. On the other hand, it may be riskier for a low growth firm to increase its financial leverage as its earnings may not increase enough to cover the additional fixed obligations. The empirical evidence for the agency theory also has been documented from the research findings of Voz and Forlong (1998), which concluded that, at the IPO stage, the IPO process performed a similar role to debt in reducing agency costs, and consequently, debt loses much of its agency advantage. Instead, the tax advantage of debt appears to be extremely significant in determining an IPO firm optimal debt level. Meanwhile, the mature-listed stage is associated with an increase in debt levels which appear to be in response to a new ownership structure. It appears that there is a very strong agency advantage of debt which surpasses the tax advantage. However, if a firm's growth options are high, this agency advantage appears to be outweighed by the need to maintain financial slack. Overall, they show the findings that debt has a significant but minor agency advantage (defined as reducing agency costs of equity) at the IPO stages and a significant advantage at the mature listed stage. 53

54 4. CONCEPTUAL FRAMEWORK 4.1 Conceptual Framework for Research Question 1a, 1b, 1c, 1d, and 1e Conceptual framework is a schematic research model to help researchers answering the research problems based on theory and relevance previous research. We formulate our conceptual framework for hypotheses 1, 2, 3, and 4 as follows: Previous Research regarding Capital Structure Determinants The variables that we tested regarding the determinants of capital structure are including collateral value of assets, growth, profitability, earning volatility, and size. Then, we draw the figure of conceptual framework for research questions 1a, 1b, 1c, 1d, and 1e. Based on our conceptual framework for research questions 1a, 1b, 1c, 1d, and 1e, we analysed the previous research findings for each variable. Figure 4.1. Conceptual Framework for Research Question 1a, 1b, 1c, 1d, and 1e Determinants of Capital Structure Growth Based ontheories of Capital Structure : - Pecking Order Theory - Trade-Off Theory Profitability Risk Size Tangibility Debt Ratio: short-term leverage, longterm leverage, total leverage, and market leverage Independent Variables Dependent Variables Growth Opportunities Sogorb-Mira and López-Gracia (2003) tested leverage predictions of the trade-off and pecking order models. They used panel data to test the empirical hypotheses over a sample of 6482 Spanish SMEs during the five-year period between 1994 and Their results showed a positive and statistically significant impact between growth opportunities and firm leverage. This result is consistent with the Michaelas et al. (1999) argument, based on the idea that in SMEs the trade off 54

55 between independence and financing availability is more pronounced and the major part of debt financing is short term. Sogorb-Mira and López-Gracia (2003) argued that this positive sign could be affected by the proxy used to measure growth opportunities (the proportion represented by intangible assets over total assets), which included, according to Spanish accounting rules, a large proportion of tangible assets, such as assets financed by leasing, patents, trademarks, etc., and therefore constituted an imperfect measure of the cited variable. According to the study of Huang and Song (2002), which contains the market and accounting data from more than 1000 Chinese listed companies up to the year 2000, to document the characteristics of these firms in terms of capital structure, concluded that the static trade-off model seemed better than pecking order hypothesis in explaining the features of capital structure for Chinese listed companies. They used sales growth rates to measure the past growth experience and Tobin s Q to measure a firm s growth opportunity in the future. Their finding showed that firms with a high growth rate in the past tended to have a higher leverage, while firms that had a good growth opportunity in the future (a higher Tobin s Q) tended to have a lower leverage. They further explained that firms with brighter growth opportunity in the future preferred to keep leverage low so they would not give up profitable investment because of the wealth transfer from shareholders to creditors, also the fast growth firms meant that these firms had good investment opportunities in the past and had used more debt to finance their investment 1. Pandey (2001) examined the determinants of capital structure of Malaysian companies using data from 1984 to He classified data into four sub-periods that corresponded to different stages of the Malaysian capital market. Debt was decomposed into three categories: short-term, long-term, and total debt. Both book value and market value debt ratios were calculated. The results of pooled OLS regressions showed that growth variable had positive significant influence on all types of book and market value debt ratios. This finding supports both trade-off and pecking order theories. He further explained that Malaysian firms have higher shortterm than long-term debt ratios. Thus, it seems that they employ short-term debt to finance their growth. Sbeiti (2010) found a negative relation between growth opportunities and leverage and it was consistent with the predictions of the agency theory that high growth firms used less debt, since they did not wish to be exposed to possible restrictions by lenders. His explanation was that growing firms had more options of choosing between risky and safe sources of funds and managers as agents to shareholders went for risky projects in order to maximise the return to their shareholders. Creditors, however, would be reluctant to provide funds to such firms as they would bear more risk for the same return. They would thus demand a higher premium from growing firms. Faced with this prospect and in order to avoid the extra cost of debt, growing firms will tend to use less debt and more equity. Hence, the relatively large magnitude of the growth coefficient may be indicative of a higher degree of information asymmetries in these markets, restricting the ability of managers to raise external debt capital. He further explains that it is also important to note that the firm-specific coefficients (such as size, liquidity, profitability and tangibility) are almost identical. However, variables such as market to book ratio reflect the capital market valuation of the firm, which in turn is affected by the conditions of the capital market. 1 The Determinants of Capital Structure: Evidence from China Samuel G. H. Huang and Frank M. Song 55

56 Shah and Khan (2007) found that growth variable was significant at a 10% level and was negatively related to leverage. As they expected, this negative coefficient of showed that growing firms did not use debt financing. They concluded that their results were in conformity with the result of Titman and Wessels (1988); Barclay, et al. (1995) and Rajan and Zingales (1995). They explained that growing firms had more options of choosing between safe and risky firms. Managers, being agent to shareholders, would try to go for risky projects and increased return to shareholders. Creditors would be unwilling to give funds to such firms as they would bear more risk for the same return. To compensate for the additional risk in growth companies, creditors would demand a risk premium. Facing extra cost of debt, growing firms would use less debt and more equity. Shah and Khan (2007) further explained that, since growing firms ran more risk of project failure as compared to businesses that were static and were run in conventional ways, managers might not want to add financial risk in addition to the high operational risk of the new projects. Thus, the managers' unwillingness to add financial risk to firm resulted in lower debt ratio for growing firms. Çağlayan and Şak (2010), on the other hand, found that market to book has positive effect on book leverage found that market to book has positive effect on book leverage. A positive sign of the market to book was also along the lines of the pecking order theory. They explained that theoretical expectations about the relationship of size and leverage, on the other hand, was ambiguous. Han-Suck Song (2005) either expected a positive relationship between expected growth and leverage, due to higher demand for funds, or a negative relationship, due to higher costs of financial distress. However, the results they obtained here showed that there existed no relationship between expected growth and leverage that was of economic significance. They indicated that one possible explanation might be the effects of the two different theories neutralising each other, the measurement used here, the percentage changed in total assets did not reflect future growth possibilities, only past growth. Thus, other more significant results might be obtained by using another measure for expected growth, for instance market-to-book ratio, a commonly used proxy for expected growth. The study of Gaud, Jani, Hoesli and Bender (2003), found the negative sign of growth and confirmed the hypothesis that firms with growth opportunities were less levered. To analyse this relationship further, they divided their sample in two sub-samples using the median growth as cut-off. The negative sign and significance of the coefficient remained irrespective of the leverage measure for the high growth firms. Concerning the low growth firms, which were typically no growth firms as the market-to-book ratio was below one, they observed a negative relationship between growth and leverage when market values were used, and a positive relation when leverage was measured with book values. Drobetz and Fix (2003) tested leverage predictions of the trade-off and pecking order models using Swiss data. They found that firms with more investment opportunities applied less leverage, which supported both the trade-off model and a complex version of the pecking order model. They found that among all proxy variables, the strongest and most reliable relationship was between investment opportunities and leverage. They explained that companies with high marketto-book ratios had significantly lower leverage than companies with low market-to-book ratios. Their result was consistent with both the trade-off theory and the extended version of the pecking order theory. Sogorb-Mira and López-Gracia (2003) tested leverage predictions of the trade-off and pecking order models using Spanish data. They found that firms with more investment 56

57 opportunities applied less leverage, which supported both the trade-off model and a complex version of the pecking order model. According to Pandey (2001), the multivariate-pooled OLS regression results showed that the coefficient of investment opportunity (market-to-book value ratio) variable was insignificant throughout. This contradicted the pecking order theory of Myers (1977, 1984) that suggested that companies with high market-to-book value would have lower long-term debt ratios because of the problem of under-investment. However, his correlation matrix showed that investment opportunity variable had inverse relation with book and market value short-term debt and long-term debt ratios. He explained that correlation implied firms with larger investment opportunities were perceived by lenders to have higher risk (bankruptcy costs). Therefore, our hypothesis 1 is as follows. Hypotheses 1a: As implied by the trade-off theory and the pecking order theory, we hypothesise that growth opportunity is positively related to debt ratios. Profitability Drobetz and Fix (2003) tested leverage predictions of the trade-off and pecking order models using Swiss data. Their results confirmed the pecking order model but contradicted with the trade-off model, more profitable firms used less leverage. They found that profitability was negatively correlated with leverage, both for book and market leverage. This result reliably supported the predictions of the pecking order theory. According to Huang and Song (2002), the results were consistent with the predictions of theoretical studies and the results of previous empirical studies. Profitability had strong negative relation with total liabilities ratios. Pandey (2001) results showed that profitability had a significant inverse relation with all types of book and market value debt ratios. He showed that the results confirmed findings of earlier studies and were consistent with pecking order theory (Myers, 1984) that postulated a negative relationship between profitability and debt ratio. The negative relationship between profitability and debt ratios contradicted with the tax shield hypothesis. He also showed that profitability seemed to be the most dominant determinant of debt ratios of Malaysian firms as it generally had high beta coefficients and t-statistics that were significant at 1% level of significance. Rebel A. Cole (2008) measured profitability by the winsorised return on assets, and showed a consistent negative relation with the loan-to-asset ratio. The coefficients for ROA were significant at the 0.05 level for three of the four surveys, with 1998 being the exception. As a robustness test, they replaced return on asset with a simple zero-one indicator for profitable firms. They found that this variable had a negative and highly significant coefficient in each of the four surveys. These latter findings were strongly supportive of the pecking order theory, which predicted that profitable firms used less debt because they could fund projects with retained earnings, but it was inconsistent with the trade-off theory, which predicted that profitable firms used more debt to take advantage of the debt tax shield, and because they had lower probability of financial distress. Sbeiti (2010) found that firm profitability seemed to have a statistically negative and significant relationship with both the book and market leverage in the three countries. The negative coefficient of profitability was indicative of the presence of informational asymmetries which could lead to higher external financing premiums and pecking order behaviour under which 57

58 firms preferred internal financing from external, but it may also support the view that the lack of well-developed financial markets forces firms to rely mostly on internal financing. He further explained that the latter explanation was consistent with Booth et al. (2001) who reported the same results for the profitability variable and argued that the importance of profitability was related to the significant agency and informational asymmetry problems in developing countries. Booth et al. (2001) indicated that it was also possible that profitability was correlated with growth opportunities so that the negative correlation between profitability and leverage, proxied the difficulty in borrowing against intangible growth opportunities. Thus, firms that generated relatively high internal funds generally tended to avoid gearing. The results were also consistent with Titman and Wessels (1988), Rajan and Zingales (1995), Cornelli et al. (1996), Bevan and Danbolt (2002) in developed countries, Pandey (2001), Um (2001), Wiwattanakantang (1999), Chen (2004), Deesomsak, Paudyal and Pescetto (2004) and Antoniou et al. (2007). In the Shah and Khan (2007) study, the most important explanatory variable was beyond doubt the profitability variable which had a very high t-statistics of and p-value of The coefficient was The negative sign and statistical significance validated the acceptance of our fourth hypothesis. The prediction of information asymmetry hypothesis by Myers and Majluf (1984) was approved by the negative sign whereas the predictions of bankruptcy theory and free-cash flow hypothesis by Jensen (1984) were not substantiated. It was thus proved that the pecking order theory dominated trade-off theory. Frydenberg (2001b) describes retained earning as the most important source of financing. Good profitability thus reduces the need for external debt. Shah and Khan (2007) explanations were as follows: One possible bias in the finding could come from the fact that many firms were family controlled in Pakistan. They inflated the cost of production and the controlling shareholders took out profit in forms other than dividend. The result was the unreal negative profit figure in income statement. The year to year negative profit figure reduced the owner s equity and increased the debt percentage in overall financing. In their initial sample, 32% of all observations for profit were negative. Even though they removed outliers from our analysis that were 3 standard deviations from the overall mean, still they had a 20.1% negative observation for the profitability variable. This was also evident from the fact that the average profitability ratio was negative for four industries in the sample years. To check for this bias, they removed all observation of negative profitability and ran regression, the coefficient for profitability was still negative, but this time the p-value was 0.83 against a very small t-value of This showed that profitability has no significant relationship with leverage. This is why the results of their main regression model should be interpreted with care with regard to profitability. In the Çağlayan and Şak (2010) study, the paper examined the capital structure of banks, from the perspective of the empirical capital structure literature, for non-financial firms by using the panel data analysis method ; investigated which capital structure theories could explain the capital structure choice of the banks; and identified two sub-periods to determine the differences across determinants of capital structure in the different periods for Turkish banks after the financial crises and restructuring periods. Their findings showed that profitability was found to have negative effect on the book leverage. A negative relationship between profitability and leverage was observed in the majority of empirical studies. This study provided similar results confirming the pecking order theory rather than static trade-off theory. In the Han-Suck Song (2005) study, they found that profitability was negatively correlated with all three leverage measures, which was in line with the pecking-order theory; firms preferred using surplus generated by profits to finance investments. Han-Suck Song (2005) explained that the result might also indicate that firms in general preferred internal funds rather 58

59 than external funds, irrespective of the characteristic of an asset that should be financed (e.g. tangible or non-tangible asset). Gaud, Jani, Hoesli, and Bender (2003) concluded that as reported in several other studies, the profitability variable was negative and significant in all cases (Rajan and Zingales, 1995; Booth et al., 2001; Frank and Goyal, 2002). This finding provides support for the pecking order theory. As the contradiction of the pecking order theory and the trade-off theory and also previous research findings, we hypothesise that: Hypothesis 1b: As the pecking order hypothesis, we hypothesise that profitability has a negative relationship with debt ratios and, based on the trade-off theory, we hypothesise that profitability has a positive relationship with debt ratio. Risk Drobetz and Fix (2003) found, as expected, the relationship between leverage and volatility negative. They also showed that their finding supports both the trade-off theory (more volatile cash flows increased the probability of default) and the pecking order theory (issuing equity was more costly for firms with volatile cash flows). Huang and Song (2002) results showed that there was the positive relation between total liabilities ratio and volatility. It was consistent with Hsia s (1981) view that firms with higher leverage level tended to make riskier investment. They found that the companies with high leverage in China tended to make riskier investments. They further explained that in China, the credit market was still regulated and the term structures of interest rates were decided by the central bank rather than by the market force such as the borrower s credibility. Banks only had the right to decide whether borrower s application was approved or not and the listed companies generally were regarded as best companies in China. As a result, the companies with high business risk still could get bank loans at regulated interest rate, which was lower than market rate if interest rate was deregulated. Pandey (2001) found that there was a negative relation of earnings volatility with book and market value long-term debt ratio, which was consistent with the trade-off theory. And it also revealed a positive relation between risk and short-term debt ratios. In Shah and Khan (2007) study, the coefficient for earning volatility was and had a very large p-value of They explained that volatility of income had no impact on the debt level. The magnitude of earning volatility was a sign of expected bankruptcy. Firms with higher volatility were considered risky because they could go bankrupt. The cost of debt for such firm should be more and thus, these firms would employ low level of leverage. They further added that court processes were slow in Pakistan and there were very few cases of bankruptcy, this could be the possible explanation for the insignificant relationship between earning volatility and leverage. Creditors did not consider the income source or the variation in income for the repayment of loan and interest by the firm. They relied more on the security of fixed assets. Han-Suck Song (2005) revealed that the effect of income variability on debt was approximately zero, but still statistically significant. Lööf (2003) also obtained similar results, according to him, this might be due to the fact that the time period studied (1991 to 1998; this study: 1992 to 2000) coincided with a period of strong economic recovery and a generally positive trend in revenues. Gaud, Jani, Hoesli and Bender (2003) concluded that the positive impact of risk for the fixed effects estimation when using market data implied that firms, which performed below 59

60 average, were less levered. In other words, companies with a high operating risk tried to control total risk by limiting financial risk. Based on the same prediction of the theories but with slightly different reason, our hypothesis is as follows. Hypotheses 1c: In accordance with the pecking order theory and trade-off theory, we hypothesise a negative relationship between risk (earnings volatility) and debt ratio. Size Drobetz and Fix (2003) found that size was positively related to leverage, indicating that size was a proxy for a low probability of default. However, the estimated coefficients on size were generally not significant. They also found that it was in contrast to the results in Rajan and Zingales (1995), where firms in Germany tended to be liquidated more easily than in the Anglo- Saxon countries. Large firms had substantially less debt than of small firms. Therefore, Drobetz and Fix (2003), interpreted their results for Switzerland as size being a proxy for low expected costs of financial distress, where small firms in Switzerland were especially wary of debt. Again, they concluded that this result supported the trade-off theory, suggesting that large firms exhibited lower probability of default. Sogorb-Mira and López-Gracia (2003) found that firm size and leverage were found to be positively related. They explained that this relationship could come from the fact that smallmedium enterprise (SMEs) had to face higher bankruptcy costs, greater agency costs and bigger costs to resolve the higher informational asymmetries. Even within this firm category, SMEs of greater size could access a higher leverage. They also found that this result was the same as that obtained by a considerable number of previous studies (Ocaña et al., 1994; Hutchinson, 1995; Chittenden et al., 1996; Berger and Udell, 1998; Michaelas et al., 1999; Romano et al., 2000). Huang and Song (2002) concluded that, on the relationship between size and leverage, if size was interpreted as a reversed proxy for bankruptcy cost, it should have less or no effect on Chinese firms leverage because the state kept around 40% of the stocks of these firms and, because of soft budget constraint, state-controlled firms should have much less chance to go bankrupt. They argued that although the state was still a controlling shareholder for most listed firms, these firms were limited corporations; it was unlikely that the state would bail them out, even in case of trouble, because the central government was only a legal representative of state shareholder. The beneficiaries of state shares in these listed firms might be local governments, who could behave just like big private shareholders. They believed the economic force worked quite well even in an environment where the state was the controlling shareholder. Pandey (2001) found that size was positively related to all types of book and market value debt ratios and all of coefficients were significant at 0.01level of significance. He showed that the positive correlation between size and debt ratios confirmed the hypothesis, that larger firms tended to be more diversified and less prone to bankruptcy and the direct cost of issuing debt or equity was smaller. This is consistent with the trade-off theory. Rebel A. Cole (2008) investigated firm size, as measured by the natural logarithm of total assets, and found size was inversely related to firm leverage, and this relation was significant at better than the level in each survey. He explained that larger firms used significantly less debt in their capital structure, and his result was at odds with what Frank and Goyal (2006) cited as one of the core set of seven factors that are correlated with cross-sectional differences in leverage. Cross-sectional studies of publicly traded firms found that leverage was robustly 60

61 related to firm size, as measured by the log of assets. He added that, clearly, this result did not hold for privately held firms. This result also is inconsistent with the trade-off theory, which predicts larger firms should use more leverage than smaller firms. Sbeiti (2010) investigated the determinants of capital structure in the context of three GCC countries and the impact of their stock markets' developments on the financing choices of firms operating in these markets. He found that the coefficient values of the size variable remained positive and were statistically significant in relation to both book and market leverage ratios across the three countries. These results confirmed the importance of the size variable as a determinant of the capital structure decisions of firm operating in the GCC markets. He added that his result was in line with the results reported by Rajan and Zingales (1995), Wiwattanakantang (1999), Booth et al. (2001), Pandey (2001), Prasad et al. (2001), Deesomsak, Paudyal and Pescetto (2004), Antoniou et al. (2007), the size of the coefficient was positive and statistically significant in the case of all three countries and for both measures of leverage. He explained that these results were consistent with the theoretical prediction that larger firms tended to be more diversified, less prone to bankruptcy with smaller direct cost for issuing debt or equity. If size was a proxy for the inverse probability of bankruptcy, then the positive relation between size and leverage complied with the predictions of the trade-off theory. This is because larger firms can diversify their investment projects on a broader basis and limit their risk to cyclical fluctuations in any one particular line of production. Moreover, informational asymmetries tend to be less severe for larger firms than for smaller ones; hence, larger firms find it easier to raise debt finance. It is also noticed that size seems to have only a limited impact on the capital structure of firms in Oman as compared to Kuwaiti and Saudi Arabia firms. This result may indicate smaller differences in informational asymmetries between large and small companies in Oman. In Shah and Khan (2007) study, size had a positive coefficient but was insignificant, with the coefficient value of , the very small t-value of 0.07, and the p-value of They showed that size variable was not a proper explanatory variable of debt ratio. Their second hypothesis was based on the Rajan and Zingales (1995) argument that there was less asymmetric information about the larger firms which reduced the chance of undervaluation of new equity. Their finding did not confirm to the Titman and Wessels (1988) argument as well that larger firms were more diversified and have lesser chances of bankruptcy that should motivate the use of debt financing. Shah and Khan (2007) explained why their finding on size of a firm with relation to the leverage ratio did not confirm to the established theories. Trade off theory suggested that firm size should matter in deciding an optimal capital structure because bankruptcy costs constituted a small percentage of the total firm value for larger firms and greater percentage of the total firm value for smaller firms. As debt increased the chances of bankruptcy, hence smaller firms should have lower debt ratio. In case of Pakistan, the court process was very slow. Negative equity figure in the balance sheet of a firm year after year and the firm still managed to survive. Among total observations of equity figure, 15% were in negative. This meant that firms were not much fearful of bankruptcy. They managed to survive even with negative equity figure. In the given scenario, size was not a matter. Facing no or very low bankruptcy costs, firms would employ debt regardless of its size. They further explained that initial public offerings are negligible in Pakistan both for small and large firms. There were only a few cases of selling ownership in government owned enterprises to public in the recent past. It meant that size was not the determinant of new equity 61

62 issue rather other factors like family control, capital market development, managerial control, etc., determine the issue of new equity. Hence, Shah and Khan (2007) concluded that size should not necessarily be a significant determinant of leverage ratio. Rajan and Zingales(1995) argued that the problem of undervaluation of new equity issue for large firm was not severe as there was less information asymmetry about them. Hence size should be negatively related to leverage. Çağlayan and Şak (2010) research concluded that size was found to have positive relationships with the leverage of banks. The findings of the relationship with the size were in line with the static trade-off and agency cost theory. In the Han-Suck Song (2005) study, the result revealed that size was a significant determinant of leverage. They explained that while size was positively related to both total debt and short-term debt ratio, it was negatively correlated with long-term debt ratio, although, the economic significance was rather small for the latter case. They added that even if the data did not allow them to further decompose short-term debt, they might still find the results of Bevon and Danbolt (2000) interesting. They found that while size was positively correlated with both trade credit and equivalent and short-term securitized debt, it was negatively correlated with short-term bank borrowing. This might indicate that small firms were supply constrained, in that they did not have sufficient credit ranking to allow them to long-term borrowing. Gaud, Jani, Hoesli, and Bender (2003) analysed the determinants of the capital structure for a panel of 106 Swiss companies listed in the Swiss stock exchange. Both static and dynamic tests were performed for the period They found that the size of companies, the importance of tangible assets and business risk were positively related to leverage, while growth and profitability were negatively associated with leverage. The sign of these relations suggested that both the pecking order theory and trade off hypothesis were at work in explaining the capital structure of Swiss companies, although more evidence existed to validate the latter theory. Their analysis also showed that Swiss firms adjusted toward a target debt ratio, but the adjustment process was much slower than in most other countries. Gaud, Jani, Hoesli, and Bender (2003) found positive impact of size on leverage. They explained that it was consistent with the results of many empirical studies (Rajan and Zingales, 1995; Booth et al., 2001; Frank and Goyal, 2002). It led them to reject the hypothesis that size acted an inverse proxy for informational asymmetries, but could suggest that size acted an inverse proxy for the probability of bankruptcy. They added that the variable size was not significant any more when leverage was computed with long-term debt only. One possible explanation from them was that large companies had easier access to the bond markets (Ferri and Jones, 1979). The development of financial markets has pushed large companies to search for better credit conditions. Consequently, there has been a tendency for banks to grant more loans to small and medium size companies. The market for short term debt securities is not well developed in Switzerland. This allows banks to select between borrowers. As banks will prefer large firms to small ones, the sign of the size coefficient is positive. For these differences, we test the following hypothesis. Hypotheses 1.d: As suggested by the trade-off theory, we hypothesise that size has a positive relationship with debt ratio, and as suggested by the pecking order theory of the capital structure there is a negative relationship between debt ratio and size. Tangibility 62

63 Drobetz and Fix (2003), found that tangibility was almost always positively correlated with leverage. They showed that the regression coefficient on tangibility was significant in about half of all regressions and this supported the prediction of the trade-off theory that the debtcapacity increased with the proportion of tangible assets on the balance sheet. Sogorb-Mira and López-Gracia (2003) tested leverage predictions of the trade-off and pecking order models using Spanish data. They showed that at an aggregate level, leverage of Spanish firms was comparatively low, but the results depended crucially on the exact definition of leverage. The result confirmed the pecking order model but contradicted with the trade-off model. Huang and Song (2002) found that, in contrast to theoretical predictions, tangibility was negatively related with total liability. They explained that the reason for that might be the non-debt part of total liability did not need collaterals. Long-term debt ratio was positively correlated with tangibility. Pandey s results (2001) indicated a significant negative relation of tangibility (fixed asset to-total asset ratio) with book and market value short-term debt ratios. The relation of tangibility with the market value long-term debt ratio was also significantly negative while with the book value long-term ratio, it was not statistically significant. These results contradicted the trade-off theory that postulated a positive correlation between long-tem debt ratio and tangibility since fixed assets act as collateral in debt issues. He also concluded that his results were consistent with DeAngelo and Masulis (1980) who suggested an inverse correlation between tangibility and debt ratio. Rebel A. Cole (2008) studied the tangibility, as measured by the ratio of property, plant and equipment to total assets. The result was positive across each of the four surveys and was statistically significant at better level than the 0.05 level for each survey except for the result in The coefficients ranged from to 0.171, indicating that a 100 basis point increased in the tangible asset ratio was associated with a 7.3 to17.1 basis point increase in the loan-to-asset ratio. According to Frank and Goyal (2006), the relation between tangibility and leverage was reliably positive in cross-sectional studies of publicly traded firms. Their results for privately held firms were broadly consistent with this finding. Sbeiti (2010) found that the stylized fact that the tangibility variable was positively related to the availability of collateral and leverage was not consistent with the findings in the paper, where tangibility was negative and statistically significant in relation to both book and market value of leverage in the three countries. She added that this negative association between leverage and tangibility could be explained by the fact that those firms that maintained a large proportion of fixed assets in their total assets tended to use less debt than those which did not. This could be due to the fact that a firm with an increasing level of tangible assets might have already found a stable source of income, which provided it with more internally generated funds and avoided using external financing. She further explained that another explanation for this relationship could be the view that firms with higher operating leverage (high fixed assets) would employ lower financial leverage, and overall the results were consistent with Cornelli et al. (1996), Hussain and Nivorozhkin (1997), Booth et al. (2001), and Nivorozhkin (2002) who also suggested a negative relation between tangibility and debt ratio. Finally, the relatively larger coefficient value of tangibility for the Saudi firms might indicate that firms in this country had an effective guarantee against bankruptcy. In Shah and Khan (2007) study, they used two variants of panel data analysis, attempted to find the determinants of capital structure of listed none-financial firms for the period Pooled regression analysis was applied with the assumption that there were no industry or 63

64 time effects. They used six explanatory variables to measure their effect on leverage ratio. Three of their variables were significantly related to leverage ratio whereas the remaining three variables were not statistically significant in having relationship with the debt ratio. Their results approved the prediction of trade-off theory in case of tangibility variable whereas the earning volatility and depreciation variables failed to confirm to trade-off theory. The growth variable confirmed the agency theory hypothesis whereas profitability approved the predictions of pecking order theory. Size variable neither confirmed to the prediction of trade-off theory nor to asymmetry of information theory. Shah and Khan (2007) found that tangibility, with a coefficient of was significantly related to debt. It had the second highest t-value of 5.56 against a very low p-value of This showed that tangibility was one of the most important determinants of leverage ratio in Pakistan. Thus their first hypothesis was confirmed by the statistically significant positive relationship between tangibility and leverage. This finding was in contrast to the earlier finding by Shah and Hijazi (2004). They found that tangibility was not significantly related to leverage ratio. Çağlayan and Şak (2010) investigated the relationship between tangibility and book leverage, and it was found to be negative in this study. They explained that this significant negative relationship between tangibility and leverage provided further support for the agency cost theory and the existence of conflict between debt holders and shareholders. In Han-Suck Song (2005) study, the paper analysed the explanatory power of some of the theories that have been proposed in the literature to explain variations in capital structures across firms. In particular, this study investigated capital structure determinants of Swedish firms based on a panel data set from 1992 to 2000 comprising about 6000 companies. Swedish firms were on average very highly leveraged, and furthermore, short-term debt comprised a considerable part of Swedish firms total debt. An analysis of determinants of leverage based on total debt ratios might mask significant differences in the determinants of long and short-term forms of debt. Therefore, their paper studied determinants of total debt ratios as well as determinants of short-term and longterm debt ratios. The results indicated that most of the determinants of capital structure suggested by capital structure theories appeared to be relevant for Swedish firms. The coefficients of tangibility are highly statistically significant for all three debt measures. But while the results show that tangibility has a positive relationship with total debt ratio and long-term debt ratio, as expected according to the theoretical discussion above, tangibility is negatively related to the short-term debt ratio. This finding is consistent with the results of Bevan and Danbolt (2000), Huchinson et al. (1999), Chittenden et al. (1996) and the Van der Wijst and Thurik (1993) report (see also Michaleas et.al., 1999). Gaud, Jani, Hoesli, and Bender (2003) concluded that the coefficient of the TANG variable was positive and significant for the panel data estimations, and this result was similar to those reported in previous research (Rajan and Zingales, 1995; Kremp et al., 1999; Frank and Goyal, 2002). Their result suggested that firms used tangible assets as collateral when negotiating borrowing, especially long term borrowing. The observed sign of the relationship did not confirm the sign that would be expected when using the pecking order theory framework. In such a framework, firms with smaller tangible assets were more subject to informational asymmetries, and were more likely to use debt - principally short term debt - when they needed external financing. Our hypothesis, based on theory and previous research, is as follow. 64

65 Hypotheses 1e: In accordance with the trade-off theory, we hypothesise a positive relationship between asset tangibility and debt ratio Conceptual Framework for Research Question 2 The variables that we tested regarding the choice of capital structure as implied by the pecking order theory are including retained earning, net debt issue, net equity issue, and debt to repurchase equity. Then, we construct the figure of conceptual framework for research questions 2. Based on our conceptual framework for research questions 2, we analysed the previous research findings for each variable. The relationship between variables is shown by the following figure. Figure 4.2 Conceptual Framework for Research Question 2, 3a, 3b, and 3c Financing Decision Internal Financing External Financing Based on Theories of Capital Structure : - Pecking Order Theory - Trade-off Theory - Signalling Theory - Asymmetric Information Debt Equity Issue Debt to Repurchase Equity Firm s Stock Price Independent Variables Dependent Variables The pecking order theory states that changes in debt have played an important role in assessing the pecking order theory. This is because the financing deficit is supposed to drive debt according to this theory. Shyam-Sunder and Myers (1999) examined how debt responded to shortterm variation in investment and earnings. The theory predicted that when investments exceeded earnings, debt grew, and when earnings exceeded investments, debt fell. Tests of the pecking order theory defined financing deficit as investments plus change in working capital plus dividends less internal cash flow. The theory predicted that in a regression of net debt issues on the financing deficit, the estimated slope coefficient should be one. The slope coefficient indicated the extent to which new debt issues were explained by financing deficits. 65

66 Shyam-Sunder and Myers found strong support for pot prediction in a sample of 157 large firms. The coefficient was 0.75 with an R 2 of They interpreted this evidence to imply that pecking order was an excellent first order descriptor of corporate financing behavior (Shyam-Sunder and Myers, 1999). Previous research from Indonesia, Ari Christianti (2008), concluded that: (1) The results of this study did not fully support the pecking order theory in explaining the behaviour of firms financing in the Indonesia Stock Exchange (IDX) especially the manufacturing sector. This could be explained from the results of the estimation that showed a negative and significant coefficient of pecking order. (2) It may be explained from the results of this study, is the Indonesian capital market conditions that are different from capital markets in developed countries studied by Shyam-Sunder and Myers (1999), Frank and Goyal (2003) and Jong, Verbeek, and Verwijmeren (2005). In addition, the impact of economic crisis in 1997 still affected the economic condition of Indonesia until Previous research from other country: Leary and Roberts (2005) empirically examined the pecking order theory of capital structure using a new empirical model that was motivated by the pecking order's decision rule and implied financing hierarchy. A power study of their associated hypothesis test revealed that the test could distinguish pecking order behaviour from non-pecking order behaviour, as well as quantify the degree to which firms adhered to the financing hierarchy. They found that 62% (29%) of the firms in the sample were following the pecking order in their decision between internal and external (debt and equity) financing and that most of the equity issuing violations were not due to debt capacity concerns, as suggested by the modified version of the pecking order. Leary and Roberts (2005) showed empirically that the pecking order did not seem to be an implication of information asymmetry. Francisco Sogorb-Mira and José López-Gracia (2003) explored two of the most relevant theories that explained financial policy in small and medium enterprises (SMEs): pecking order theory and trade-off theory. Panel data methodology was used to test the empirical hypotheses over a sample of 6482 Spanish SMEs during the five-year period Their results suggested that both theoretical approaches contributed to explain capital structure in SMEs. However, while they found evidence that SMEs attempted to achieve a target or optimum leverage (trade-off model), there was less support for the view that SMEs adjusted their leverage level to their financing requirements (pecking order model). Cotei and Farhat (2008) investigated the models used in testing the trade-off and pecking order theories. Specifically, for the pecking order theory, they examined the symmetric behaviour assumption. For the pecking order model, the test results rejected the symmetric behaviour assumption at the industry level as well as across all industries. Under the pecking order model, firms in financing deficit used debt to finance their new investment, whereas firms in financing surplus ended up retiring debt rather than repurchasing equity. Hence, their results showed that for the pecking order model, they rejected the hypothesis that firms had a symmetric behaviour regardless of the sign of the financing variable. Their results showed that firms had the tendency to reduce debt by a significantly higher proportion when they had financing surplus compared to the proportion of debt issued when they had financing deficit. Joher, Ahmed, and Hisham (2009) paper drew on studies from finance and accounting literature to revisit pecking order and static trade-off-hypothesis in the context of the Malaysia capital market, using a sample of 102 list firms over a four-year time frame ( ). Their evidence from the pecking order model suggested that the internal fund deficiency was the most important determinant that possibly explained the issuance of new debt. Hence, the pecking order 66

67 hypothesis was well explained in the Malaysian capital market despite the lower predicting power. This could be the evidence from both pecking order models that exhibited a significant coefficient for financing deficit, significant at the conventional level, but with very low R 2. To address this issue of low predicting power, the pecking order model was expanded by including the component of internally generated fund deficiency such as dividend, debt repayment, capital expenditure, investment on working capital and operating cash flow. The expanded pecking order model provided more vibrant explanation for debt issuance with higher predictive power. Meanwhile, their result for static trade-off-model was not fit to explain the issuance of new debt issue in Malaysian capital market. That was an interesting findings that confirmed the fact that Malaysian firms did not too much care about tax-shield benefit derived from employing both debt and non-debt tax-shields. The firm s size, which was used to neutralise the size effect, appeared to provide some explanation for the variation in its capital structure policy choice. In the Bharath, Pasquariello, and Wu (2008) study, using a novel information asymmetry index based on measures of adverse selection developed by the market microstructure literature, they tested whether information asymmetry was an important determinant of capital structure decisions, as suggested by the pecking order theory. They found that information asymmetry did affect the capital structure decisions of U.S. firms over the sample period Overall, this evidence explained why the pecking order theory was only partially successful in explaining all of firms capital structure decisions. The Shyam-Sunder and Myers (1994) paper tested traditional capital structure models against the alternative of a pecking order model of corporate financing. The basic pecking order model, which predicted external debt financing driven by the internal financial deficit, had much greater explanatory power than a static trade-off model which predicted that each firm adjusts toward an optimal debt ratio. They summarized main conclusions regarding pot as follows: (1) The pecking order is an effective first-order descriptor of corporate financing behaviour. (2) The coefficient and significance of the pecking order variable change hardly at all. (3) The strong performance of the pecking order does not occur just because firms fund unanticipated cash needs with debt in the short run. Their results indicated that firms planned to finance anticipated deficits with debt. Medeirosa and Daherb tested two models with the purpose of finding the best empirical explanation for the capital structure of Brazilian firms. The models tested were developed to represent the static tradeoff theory and the pecking order theory. The sample consisted of firms listed in the São Paulo (Brazil) stock exchange from 1995 through By using panel data econometric methods, they aimed at establishing which of the two theories had the best explanatory power for Brazilian firms. The analysis of the outcomes led to the conclusion that the pecking order theory provided the best explanation for the capital structure of those firms. The pecking order theory established that the financial deficit was covered by debt, permitting the issue of new shares in exceptional cases only. The Frank and Goyal model stated that the deficit coefficient must be equal to zero in order to validate the strong form of the pecking order theory. Therefore, the most important test was the one which determined the value of this coefficient. The results obtained in Medeirosa and Daherb study supported the pecking order theory in its semi-strong form, since both the aggregate and the disaggregate equations were led to accept the null that the slopes were equal to one, but to reject the null that the intercepts were equal to zero. 67

68 The Lakshmi Shyam-Sunder and Stewart C. Myers (1999) paper tested traditional capital structure models against the alternative of a pecking order model of corporate financing. The basic pecking order model, which predicts external debt financing driven by the internal financial deficit, has much greater timeseries explanatory power than a static tradeoff model, which predicts that each firm adjusts gradually toward an optimal debt ratio. Instead, they view the theories as contending hypotheses and examine their relative explanatory power. The attention to statistical power is an important methodological point. They summarized the main conclusions regarding pot as follows. (1) The pecking order is an excellent first-order descriptor of corporate financing behaviour, for their sample of mature corporations. (2) The strong performance of the pecking order does not occur just because firms fund unanticipated cash needs with debt in the short run. Their results suggested that firms planned to finance anticipated deficits with debt. Therefore, our hypothesis 2 is as follows: Hypothesis 2: Firms in the manufacturing sector raise capital for investments externally (with debt, equity, or debt to repurchase equity) Conceptual Framework for Research Question 3 The variables that we tested regarding the effect of capital structure choices on stock price as implied by some theories are including firm s stock price, net debt issue, net equity issue, or issue debt to repurchase equity. Then, we construct the figure of conceptual framework for research questions 3. Based on our conceptual framework for research questions 3, we analysed the previous research findings for each variable. The relationship between variables is shown by the figure 4.2. When a firm issues, repurchases or exchanges one security for another, it changes its capital structure. There are several theories which explain the relationship between capital structure and stock price. Theories which explain the relationship between net debt and equity issue and stock price are as follow. Net Debt Issue Theories implied different implication for the issuance of new debt on firm s stock price. Ross (1977) introduces the notion of signalling in the capital structure theory. According to his theory, the managers know the true distribution of the company returns, but investors do not. He argues that higher financial leverage can be used by the managers to signal an optimistic future of the company since the debt is a contractual obligation to repay both principal and interests. The failure to make those payments could lead to bankruptcy and by consequence the managers would lose their jobs. Therefore adding more debt to the capital structure could be interpreted as a good signal of the managers optimism about their companies. The issuance that new debt will positively influence a firm s stock price is based on signalling theory through capital structure, the increased level of leverage is accompanied by higher risk of bankruptcy, the increased level of debt indicates the confidence of the management in the future prospects of the firm. Hence, it carries greater conviction than a mere announcement of undervaluation of the firm, by the management. The markets normally react favourably to moderate increases in leverage. 68

69 On the other hand, the issuance of new debt will less negatively influence a firm s stock price than the issuance of new equity, or no market reaction, is as implied by the pecking order theory. The pecking order theory is usually interpreted as predicting that securities with less adverse selection (debt) will result in less negative or no market reaction. However, under the trade-off theory, the market response to a leverage change confounds two pieces of information. Under the theory, firms will only take actions if they expect benefits. The information contained in security issuance decisions could be either good news or bad news. It would be good news if the firm is issuing securities to take advantage of a promising new opportunity that was not previously anticipated. It might be bad news if the firm is issuing securities because the firm actually needs more resources than anticipated to conduct operations. A firm may also issue securities now in anticipation of a change in future needs. This implies that the trade-off theory by itself places no obvious restrictions on the market valuation effects of issuing decisions. Everything depends on the setting. Net Equity Issue Meanwhile, based on signalling theory, agency perspective, and pecking order theory, the issuance of new equity will negatively influence a firm s stock price. As implied by signalling through capital structure, an issue of equity is a signal that the firm is overvalued. The market concludes that the management has decided to offer equity because it is valued higher than its intrinsic worth by the market. The markets normally react negatively to fresh issue of equity. Jung et al. (1996) suggested an agency perspective and argued that equity issues by firms with poor growth prospects reflected agency problems between managers and shareholders. If this is the case, then stock prices will react negatively to the news of equity issues. However, the pecking order theory is usually interpreted as predicting that securities with more adverse selection (equity) will result in more negative market reaction. Myers and Majluf (1984) assumed that company managers have always more information about the true value of the company than the other investors. Managers will therefore time a new equity issue if the market price exceeds their own assessment of the stock value if the stocks are overvalued by the market. Since investors are aware of the existence of the information asymmetry, they will interpret the announcement of an equity issue as a signal that the listed stocks are overvalued, which subsequently will cause a negative price reaction. The managers can use the information asymmetry to their profit and to reinforce their entrenchment strategy in their respective companies. Besides, they can use their informational advantage in order to get more benefits and to maximise their income (Stiglitz and Edlin, 1992). With this intention, the managers can reduce the threat of the competition of the potential managers on the labor market by two possible manners: either by setting up investments strongly dependent on their specific information, or by investing in projects with high information asymmetry. Based on the undervaluation hypothesis, stock repurchases offer flexibility not only for distributing the excess of funds but also the timing of distributing these funds. This flexibility in timing is beneficial because firms can wait to repurchase until the stock price is undervalued. The undervaluation hypothesis is based on the premise that information asymmetry between insiders and shareholders may cause a firm to be misvalued. If insiders believe that the stock is undervalued, the firm may repurchase stock as a signal to the market or to invest in its own stock and acquire mispriced shares. According to this hypothesis, the market interprets the action as an indication that the stock is undervalued (Dittmar, 1999). Because of the asymmetric information 69

70 between managers and shareholders, share repurchase announcements are considered to reveal private information that managers have about the value of the company (in Smura). The information/signalling hypothesis has three immediate implications: repurchase announcements should be accompanied by positive price changes; repurchase announcements should be followed (though not necessarily immediately) by positive news about profitability or cash flows; and repurchase announcements should be immediately followed by positive changes in the market s expectation about future profitability (in Gustavo Grullon and Roni Michaely, 2002). Some previous empirical evidence regarding to debt issue on stock price are the following: Announcements of ordinary debt issues generate zero market reaction on average (Eckbo (1986) and Antweiler and Frank (2006)). The zero market reaction to corporate debt issues is robust to various attempts to control for partial anticipation. Ross (1977) showed that good corporate performance could give a signal with a high portion of debt in their capital structure. Ross (1977) assumed the firms that are less good performance would not use debt in large portion as it would be followed by the high chance of bankruptcy. By using these assumptions in which the company will use the good performance of higher debt, while firms that are less good performance will use more of equity. Ross (1977) assumed that investors would be able to distinguish the company's performance by looking at the company's capital structure and they would give a higher value on the company with larger debt portion. It indicated that the result did not support the stating of the signalling theory. The result indicated that the greater the leverage, the greater the possibility of financial distress leading to bankruptcy. When the company went bankrupt, shareholders would lose money they have invested in the company (Peirson et al, 2002). Exchange of common for debt/preferred stock generates positive stock price reactions while exchange of debt/preferred for common stock generates negative reactions (Masulis, 1980a). Summarising the event study evidence, Eckbo and Masulis (1995) concluded that announcements of security issues typically generated a nonpositive stock price reaction. In Indonesia, the regression coefficient between leverage and stock price is significantly negative. The use of high leverage will be responded by the market with a fall in stock prices.the results are consistent with the findings of a negative relationship between leverage and stock price as proposed by Frank and Goyal (2003). Relationship between the two variables will be positive at the time the company has many tangible assets that will secure leverage of companies. Announcements of convertible debt issues result in mildly negative stock price reactions (see Dann and Mikkelson (1984) and Mikkelson and Partch (1986)). The valuation effects are the most negative for common stock issues, slightly less negative for convertible debt issues and least negative (zero) for straight debt issues. The effects are more negative the larger the issue. Some previous empirical evidence regarding the equity issue on stock price are the following: Announcements of equity issues result in significant negative stock price reactions (Asquith and Mullins Jr., 1986; Masulis and Korwar, 1986; and Antweiler and Frank, 2006). The negative market reaction to equity issues and zero market reaction to debt issues are consistent with adverse selection arguments. Indeed, there are other interpretations. Jung et al. (1996) showed that firms without valuable investment opportunities experienced a more negative stock price reaction to equity issues than did firms with better investment opportunities. Thus, agency cost arguments could also explain the existing evidence on security issues. Further support for the agency view came from the finding that firms without valuable investment opportunities 70

71 issuing equity invest more than similar firms issuing debt and that firms with low managerial ownership have worse stock price reaction to new equity issue announcements than do firms with high managerial ownership. The impact of equity issues appears to differ between countries. Several studies find positive market reaction to equity issues around the world (Eckbo et al., 2007). To understand this evidence, Eckbo and Masulis (1992) and more recently Eckbo and Norli (2004) examine stock price reactions to equity issues conditional on a firm s choice of flotation method. Firms can issue equity using uninsured rights, standby rights, firm commitment underwriting and private placements. The stock price reactions to equity issues depend on the floatation method. For U.S. firms, Eckbo and Masulis (1992) found that the average announcement-period abnormal returns were insignificant for uninsured rights offerings and they were significantly negative for firmcommitment underwritten offerings. Eckbo and Norli (2004) studied equity issuances on the Oslo Stock Exchange. They found that uninsured rights offerings and private placements resulted in positive stock price reactions while standby rights offerings generated negative market reactions. These papers interpreted the effect of the flotation method as reflecting different degrees of adverse selection problems. Some previous empirical evidence regarding the stock repurchases on stock price are as follows: Many studies show that repurchases are associated with a positive stock price reaction. Vermaelen (1981), Dann (1981), and Comment and Jarell (1991) found the positive stock price reaction at the announcement of a stock repurchase program should correct the misevaluation. Ikenberry, Lakonishok and Vermaelen (1995) showed that this increase might not be sufficient to correct the price since repurchasing firms, particularly low market to book firms, earned a positive abnormal return during the four years subsequent to the announcement. The amount of information available and the accuracy of the valuation of firms by the market could affect firms repurchase decisions. According to Jensen (1986), firms repurchased stock to distribute excess cash flow. Stephens and Weisbach (1998) supported this hypothesis, as they found a positive relation between repurchases and levels of cash flow. Stephens and Weisbach also showed that repurchase activity was negatively correlated with prior stock returns, indicating that firms repurchased stock when their stock prices were perceived as undervalued. This result agrees with Vermaelen s (1981) findings that firms repurchase stock to signal undervaluation. Thus, firms repurchase stock when they are undervalued and have the excess cash to distribute. Masulis (1980b), Dann (1981), and Antweiler and Frank (2006) also found that the announcement effects were positive when common stock is repurchased. According to Brav et al. (2005.b.) it was discovered on their survey that only 22.5 percent of executives believed that reducing repurchases had negative consequences. On the other hand, almost 90 percent thought that reducing dividends had negative consequences. Hypotheses 3: Therefore, our hypotheses 3 are as follow: (a) If firms issue new debt, then the firm s stock price will be higher. (b) If firms issue new equity, then the firm s stock price will be lower. (c) If firms issue debt to repurchase equity, then the firm s stock price will be higher. 71

72 4.1.4 Conceptual Framework for Research Question 4 The variables that we tested regarding the choice of capital structure over firm s life cycle as implied by the pecking order theory are including net debt issue, net equity issue, and issue debt to repurchase equity. Then, we construct the figure of conceptual framework for research questions 4. Based on our conceptual framework for research questions 4, we analysed the previous research findings for each variable. The relationship between variables is shown by the figure 4.3. Figure 4.3 Conceptual Framework for Research Question 4 Financial Deficit Independent Variables Capital structure over firm s life cycle as implied by Pecking Order Theory Newly Retained Earnings Net Debt Issued Net Equity Issued Dependent Variables Over firms life cycle stages : growth and mature firms Research question 4 focusses only on the pecking order theory as only the pecking order theory, which specifically explains about the specific preference order of firms capital structure over firms life cycles. It is important examining the firm capital structure over the life cycle of the firm in solving the problem of firm financing deficit. Firms in different life cycle stage have different characteristics especially regarding information asymmetry and dividend payment. Mature firms have less information asymmetry, whereas growth firms have more information asymmetry. We test hypothesis 4 to examine which firm s life cycle follow the pecking order more closely. It is the most interesting part of this research as firm in different life cycle stage has different capital structure choices by considering the characteristics, and information asymmetry as implied by pecking order theory. The empirical evidence for the pecking order theory over a firm s life cycle has been mixed. Helwege and Liang (1996) followed a sample of recent IPO firms and found that these firms decision to access the external finance markets as well as their choice of type of external finance is inconsistent with the pecking order. Shyam-Sunder and Myers (1999) proposed a direct test of the pecking order and found strong support for the theory among a sample of large firms. Frank and Goyal (2003) argued that the Shyam-Sunder and Myers test rejected the pecking order for small public firms. They concluded that this finding was in contrast to the theory since small 72

73 firms were thought to suffer most from asymmetric information problems and hence, should be the ones following the pecking order. More recent work by Lemmon and Zender (2004) and Agca and Mozumdar (2004) have shown that the Shyam-Sunder and Myers test did not account for a firm s debt capacity, a constraint that was particularly binding for small firms. Thus, it was not surprising that this test failed to find support for the pecking order among small firms. To address this shortcoming, Lemmon and Zender and Agca and Mozumdar used sub-samples of firms that were the least debtconstrained and they found support for the pecking order. In addition, once debt capacity constraints were accounted for, they found that the pecking order performed well even for small firms. Bulan and Yan (2009) examined the central prediction of the pecking order theory of financing among firms in two distinct life cycle stages, namely growth and maturity. They found that within a life cycle stage, where levels of debt capacity and external financing needs were more homogeneous, and after sufficiently controlling for debt capacity constraints, firms with high adverse selection costs followed the pecking order more closely, consistent with the theory. More importantly, they found that growth firms had greater financing deficits but smaller debt capacity. It implied that growth firms would reach their debt capacities more often than mature firms. They argued that within a broad sample of firms, inference regarding the empirical performance of the pecking order theory was weakened if differences in these two key attributes were unaccounted for in the empirical test. Their results were consistent with firms following the pecking order: the coefficient on the deficit was positive and the coefficient on the deficit-squared was negative. Both growth and mature firms were issuing debt first, while equity was the residual source of financing once they reached their debt capacities. Comparing across life cycle stages however, they found that mature firms had significantly higher debt-deficit sensitivities indicating that mature firms followed the pecking order more closely. This was contrary to conventional wisdom since they would expect growth firms to suffer more from information asymmetry problems. Bulan and Yan (2009) documented this result as a maturity effect in firm financing choice. Mature firms were older, more stable, and highly profitable with few growth opportunities and good credit histories. Hence, mature firms were able to borrow more easily and at a lower cost. Therefore, by the very nature of their life cycle stage, mature firms were pre-disposed to utilizing debt financing first before equity. Bulan and Yan (2007) studied firms financing behaviour over life cycle stages in the context of the pecking order theory. They classified firms into two life cycle stages, namely growth and maturity, and tested the pecking order theory of financing proposed by Myers (1984) and Myers and Maljuf (1984). They used two different empirical frameworks: the Shyam-Sunder and Myers (1999) model and the Leary and Roberts (2006) model. Under both specifications, they identified two effects: a size effect and a maturity effect. The size effect was consistent with Frank and Goyal (2003), who found that large firms fitted the pecking order theory better than of small firms, contrary to the predictions of the theory. However, Bulan and Yan (2007) found that this size effect existed only among firms in their growth stage. For firms in their mature stage, this size effect was not significant. When controlling for a firm s debt capacity, this size effect disappears altogether, while the maturity effect remains. Overall, Bulan and Yan (2007) found that the pecking order theory described the financing patterns of mature firms better than of growth firms. This is contrary to the theory s prediction that firms with the greatest information asymmetry problems (specifically 73

74 young, growth firms) are precisely those that should be making financing choices according to the pecking order. In general, the major difference between mature and young firms is not that mature firms are larger, but because they are more mature. Mature firms are older, more stable, higher profitable with few growth opportunities and good credit histories. They are thus more suited to use internal funds first, and then debt before equity for their financing needs. These results are robust under alternative empirical models for testing the pecking order theory. Bulan and Yan (2007) further saw that growth firms had larger financing deficits, as expected. The financing deficit is defined as the uses of funds minus internal sources of funds, which, by an accounting identity, is also the sum of net debt issued and net equity issued. There seems to be no difference in net debt issued between the two cohorts, while net equity issued is larger for the growth firms. From this simple comparison, the evidence seems to suggest growth firms rely more heavily on equity financing rather than debt. This finding is consistent with Agca and Mozumdar (2004) and Lemmon and Zender (2004). Overall, Bulan and Yan (2007) found that the pecking order theory described the financing patterns of mature firms better than that of younger growth firms. Older and more mature firms are more closely followed by analysts and are better known to investors, and hence, should suffer less from problems of information asymmetry. Furthermore, mature firms generally have more internal funds due to higher profitability and lower growth opportunities. Hence, their findings suggest that it is firm maturation, and not adverse selection, that motivates pecking order behaviour. Older, more stable and highly profitable firms with few growth opportunities and good credit histories are more suited to use internal funds first, and then debt before equity for their financing needs. Halov and Heider s (2003) starting point for the analysis was the empirical puzzle that the pecking order seems to work well when it should not, i.e., for large mature firms, and seems not to work well when it should, i.e., for small young non-payers of dividends. They argued that the original pecking order was based on the mis-pricing of equity caused by not knowing the value of investments. But when outside investors also do not know the risk of investments, then debt is mis-priced, too. They argued that asymmetric information about both, value and risk, transformed the adverse selection logic into a theory of debt and equity. Their main hypothesis was that firms issued more equity and less debt in situations where risk was an important element of the adverse selection problem of outside financing. They found robust empirical support for the hypothesis and document a strong link between asset risk and the decision to issue debt and equity in a large unbalanced panel of publicly traded US firms from 1971 to While Frank and Goyal expected the pecking order to work best for young, small firms since they argued that these firms should have the most severe asymmetric information problem, Halov and Heider (2003) explained that the standard pecking order should not work at all for young, small firms. Risk differences, i.e., differences in failure rates and upside potential play an important role in the adverse selection problem for young, small firms. Hence, they should issue equity and not debt, or alternatively, rational investors demand equity and not debt from these firms. Suarez (2005) study concluded that, the pecking order s high explanatory power could be the result of sample bias towards large and mature firms. This implies that a sample of smaller growth firms may not provide the good fit required to establish statistical power to the pecking order specification. He explained that it has been observed that even small growth firms that had 74

75 the ability to issue default free debt or venture capital (close ties with local banks) were characterized by very low levels of debt (even zero) and high levels of equity financing. He added that it would be interesting to carry out similar procedures with these models using a different firm sample (i.e. composed of small venture capital firms) to then see if the pecking order model stood the test. Frank and Goyal (2003) examined the broad applicability of the pecking order theory. Their evidence based on a large cross-section of US publicly traded firms over long time periods, showed that external financing was heavily used by some firms. On average net equity issues track the financing deficit more closely than do net debt issues. These facts do not match the claims of the pecking order theory. Frank and Goyal (2003) evidenced greatest support for pecking order that was found among large firms, which might be expected to face the least severe adverse selection problem since they received much better coverage by equity analysts. According to them, even here, the support for pecking order was declining over time and the support for pecking order among large firms was weaker in the 1990s. They concluded that the pecking order theory did not explain broad patterns in the data. Therefore, we hypothesise that, Hypothesis 4 : In the context of firm s life cycle, we expect that growth [and small] firms follow the pecking order theory more closely than mature [and large] firms. 75

76 5. RESEARCH METHODOLOGY 5.1 Research Design The objectives of this research are to investigate the determinants of capital structure of the firms in the manufacturing sector in Indonesian capital market, to analyse how firms in the manufacturing sector raise capital for investments, internally or externally (with debt, equity, or debt to repurchase equity), to examine if debt policy does matter, what will happen to the firms s stock price if firms issue new debt, issue new equity, or issue debt to repurchase equity, and to examine in the context of firm s life cycle, can we expect that growth-small-young firms follow the pecking order more closely. The study is using a combination of quantitative and qualitative approaches or strategies. The dominant strategy is quantitative. The process of the research is described as follows: Figure 5.1. Research Process Wish to do research Formulate and clarify research topic Critically review the literature Plan data collection and collect the data Research methodology, choose research approach and strategy Analyse data using both of quantitative and qualitative method Conceptual framework and hypotheses formulation Write project report and prepare presentation Submit report and give presentation Source: Mark Saunders, Phillip Lewis, and Adrian Thornhill (2003) In Mark Saunders, Phillip Lewis, and Adrian Thornhill (2003), the research process consists of 9 steps. In this research, we add an overview of capital structure of Indonesian manufacturing firms between step 1 and step 2. Step 1: We formulate and clarify the research topic, it is written to assist us in the generation of ideas, which will help to choose a suitable research topic, and offers advice on what makes a good 76

77 research topic. As soon as we have found a research topic, we refine it into one that is feasible. After the idea has been generated and refined, we turn this idea into clear research questions and objectives. This step is applied in chapter 1. Step 2: We reviewed some critical literature to outline what to include and decided on the range of primary, secondary and tertiary literature sources available. This step is applied in chapter 3. Step 3: At this step, we wrote the conceptual framework and the hypotheses formulation by analysing capital structure theories and some previous research. This step is applied in chapter 4. Step 4: We worked on the research methodology, research approach and the strategy. A clear research strategy is crucial because the credibility of research findings and conclusions depend on it. Step 5: At step five, we plan data collection which is concerned with different methods of obtaining data. Step 6: At this stage we analyse data using both of quantitative and qualitative method, outlines, and discusses the main approaches available to analyse data quantitatively. Steps 4, 5, and 6 are applied in chapter 5. Step 7: In this chapter, we write the project report and the prepare presentation with the structure, content and style of final project report and any associated oral presentations. This step is applied in chapter 6. Step 8: After we finish all of the earlier steps of the research process, we hope we will submit the research report (the thesis) and give presentation in time. 5.2Research Strategy In this research, our research strategy for hypotheses 1, 3, and 4 is quantitative strategy, while for hypothesis 2 we apply both quantitative and qualitative research strategy. The following is its analysis Quantitative Strategy In this study, we have used quantitative and combination of quantitative and qualitative approaches or strategies as all research methods have limitations. One method can be nested within another method to provide insight into different levels or units of analysis (Tashakkori and Teddlie, 1998). A quantitative approach is one in which the investigator primarily uses post-positivist claims for developing knowledge (cause and effect thinking, reduction to specific variables and hypotheses and questions, use of measurement and observation, and the test of theories), employs strategies of inquiry such as experiments and surveys, and collects data on predetermined instruments that yield statistical data (Creswell, 2003). Therefore, the following hypotheses are treated with using quantitative approach: Hypotheses 1a: As implied by the trade-off theory and the pecking order theory, we hypothesise that growth opportunity is positively related to debt ratios. 77

78 Hypotheses 1b: As in the pecking order hypothesis, we hypothesise that profitability has a negative relationship with debt ratios and based on the trade-off theory we hypothesise that profitability has a positive relationship with debt ratio. Hypotheses 1c: In accordance with the pecking order theory and trade-off theory, we hypothesise a negative relationship between risk (earnings volatility) and debt ratio. Hypotheses 1d: As suggested by the trade-off theory, we hypothesise that size has a positive relationship with debt ratio, and as suggested by the pecking order theory of the capital structure there is a negative relationship between debt ratio and size. Hypotheses 1e: In accordance with the trade-off theory, we hypothesise a positive relationship between asset tangibility and debt ratio. Hypotheses 3: (a) If firms issue new debt, then the firms s stock price will be higher. (b) If firms issue new equity, then the firms s stock price will be lower. (c) If firms issue debt to repurchase equity, then the firms s stock price will be higher. Hypothesis 4: In the context of firm s life cycle, we expect that growth [and small] firms follow the pecking order theory more closely than mature [and large] firms Mixed Method Strategy The following hypothesis 2 is analysed by using the mixed method approach to make more in-depth analysis of our results. The dominant strategy used is quantitative strategy. Hypotheses 2: Firms in the manufacturing sector raise capital for investments externally (with debt, equity, or debt to repurchase equity). 5.3 Data Collection Research samples that we used were all manufacturing companies which incorporated in the LQ45 Index, one of the index in Indonesian Stock Exchange. LQ45 consists of 45 companies with large capitalisation value. Therefore, our research samples are 26 manufacturing companies in the LQ index from the years 1994 to We collected the data from the book of data published by IDX. The book of data consists of financial statement of each firm. 78

79 Figure 5.2. Data Analysis and Collection Quantitative (QUAN) Qualitative (QUAL) QUAN Data QUAN Data Collection Analysis Source: Creswell et al. (2003) For hypothesis 2, we used the combination of quantitative and qualitative research strategy; our strategy priority was quantitative. Therefore, we only collected the quantitative data, followed by quantitative data analysis, qualitative data analysis, and interpretation of entire analysis. For hypotheses 1, 3, and 4, we used quantitative research strategy. Hence, we applied quantitative data collection followed by quantitative data analysis Sampling Design and Procedure We took all firms of the manufacturing sector in LQ45 during the period of 1994 to Then we got 26 manufacturing firms as our sample. The following figure 5.3 describes our sampling design. Figure 5.3. Sampling Design QUAL Data Collectio n QUAL Data Analysis Interpretation of Entire Analysis LQ45 Index Manufacturing Sector Non-Manufacturing Sector from the Year 1994 to the Year 2007 The JSX LQ45 Index was created to provide the market with an index that represented 45 of the most liquid stocks. To date, the LQ45 Index covers at least 70% of market capitalisation and transaction values in the regular market. The LQ45 Index historical calculation was defined at July 79

80 13, 1994, with a base value of 100. The index consists of 45 stocks that have passed the liquidity and market capitalisation screenings. Table 5.1. Research Samples Manufacturing Firms ASII GJTL KAEF AUTO HMSP RMBA ADMG INDF SMCB BRPT INDR SMGR BUDI INKP TKIM CPIN INAF TSPC DNKS INTP UNVR FASW KLBF SULI GGRM KOMI The firms in LQ45 index during that period we reviewed every 3 months and they could still stay in the list or be crossed out of the list. Hence, within sampling period, we got 26 manufacturing firms sample as shown in table above Variables Measurement Tested variables in our research were leverage, growth opportunity, profitability, risk, size, asset tangibility for H1, net debt issue, net equity issue, newly retained earning, and financing deficit for H2 and H4, and net debt issue, net equity issue, newly retained earning, and stock price for H3. The following are the measurements of the research variables Variable of Hypothesis 1 Our research variables of hypotheses 1 are including total leverage, short-term leverage, long-term leverage, and market leverage as dependent variables, while growth opportunity, profitability, risk, size, and asset tangibility as independent variables. The following sub-section is the describtion of how we measure the variables. A. Leverage The leverage of a firm can be measured by many different variables. For instance, Pandey (2001) measured leverage as market value of long term debt to total asset, market value of short term debt to total asset, market value of total debt to total asset, book value of long term debt to total asset, book value of short term debt to total asset, and book value of total debt to total asset. Chen and Hammes (2003) measured leverage as book capital ratio, and market capital ratio as primary measures of leverage, where market capital ratio was market capitalisation replacing the book equity. They used book debt ratio (total debt to total asset) as a secondary measure. We choose four debt ratios in this study. These are total leverage, short-term leverage, long-term leverage, and market leverage. These measures of debt ratios examine the capital employed and thus represent the effects of past financing decisions best. 80

81 Our measurement of book leverage is as measured by Rajan and Zingales (1995), Leary and Roberts (2005), and Sbeiti (2010), and of market leverage is as measured by Bulan and Yan (2009). TLV=TD/TA MRL = (TLV) / (TA+MV of Equity-TE) Where TLV is total leverage, MRL is market leverage, TA is total asset, MV of equity is market value of equity, and TE is total equity. B. Growth Opportunities The growth potential of a firm can be measured by many different variables. Rajan and Zingales (1995) measured growth as Tobin s Q, Laarni Bulan and Zhipeng Yan (2009) measured growth as market-to-book ratio as market equity/book equity, and Akhtar and Oliver (2006) defined it as the average percentage change in total assets over the previous four years. Chen and Hammes (2003), Leary and Roberts (2005), and Sbeiti (2010) measured growth opportunities as the ratio of market value of assets (book value of assets plus market value of equity less book value of equity) to book value of assets. We measure growth opportunities as: Growth = the ratio of market value of assets (book value of assets plus market value of equity less book value of equity) to book value of assets. C. Profitability Profitability plays an important role in leverage decisions. Profitability is proxied by return on assets. ROA represents the contribution of the firm s assets on profitability creation. Profitability is a measure of earning power of a firm. The earning power of a firm is generally the basic concern of its shareholders. Akhtar and Oliver (2006) measured profitability as the average net income to total sales for the past four years. Wafaa Sbeiti (2010) measured profitability as the ratio of operating profit to book value of total assets. Titman and Wessels (1988), Drobetz and Fix (2003) measured it as the ratio of operating income over total assets (ROA) and the ratio of operating income over sales. Chen and Hammes (2003), Rajan and Zingales (1995), Abimbola Adedeji, Francisco Sogorb-Mira y José López-Gracia (2003) measured profitability as earnings before interest and taxes divided by total asset. We measure profitability as: Profitability = earnings before interest and taxes divided by total asset. D. Risk Earnings volatility measures the variability of the firm's cash flows as a proxy for the costs of monitoring managers and of the risk of an insider's position. The use of longer time periods causes a significant loss of the sample size. 81

82 Several measures of volatility were used in different studies, such as Bradley, Jarrell and Kim (1984), Drobetz and Fix (2003) used variability as the standard deviation of the first difference in annual earnings, scaled by the average value of the firm s total assets over time, Booth et al., (2001) the standard deviation of the return on sales. Leary and Roberts (2005) measured cash flow volatility as the standard deviation of earnings before interest and taxes, however they were based on (up to) the previous 10 years of data for a given firm-year observation while we were up to the previous 3 years of data for a given firm-year observation. Risk = coefficient of variation in earnings before interest and taxes (EBIT) over three years. E. Size Firm size provides a measure of the agency costs of equity and the demand for risk sharing. Firm size is likely to capture other firm characteristics as well (e.g., their reputation in debt markets or the extent their assets are diversified). Titman and Wessels (1988) and Drobetz and Fix (2003) measured firm size as the natural logarithm of net sales. Chen and Hammes (2003) measured firm size as in Rajan and Zingales (1995) that is the natural logarithm of total turnover. Akhtar and Oliver (2006), Leary and Roberts (2005), Francisco Sogorb-Mira y José López-Gracia (2003), and Sbeiti (2010) measured size as the natural logarithm of total assets. Size = the natural logarithm of total assets. F. Tangibility The tangibility of assets represents the effect of the collateral value of assets of the firm s gearing level. There are various conceptions for the effect of tangibility on leverage decisions. If debt can be secured against assets, the borrower is restricted to using debt funds for specific projects. Creditors have an improved guarantee of repayment, but without collateralised assets, such a guarantee does not exist. Leary and Roberts (2005), Bulan and Yan (2009) measured tangibility as net property, plant and equipment divided by total assets. Huang and Song, Drobetz and Fix (2003), Abimbola Adedeji, Dilek Teker,Ozlem Tasseven, and Ayca Tukel (2009) measured tangibility as fixed assets divided by total assets. Tangibility = fixed assets divided by total assets Measuring Variables of Hypotheses 2, 3, and 4 A. Financing Deficits Bharath, Pasquariello, and Wu (2008) measure firms financing deficits, dividends, investments, and cash flow separately. Frank and Goyal (2003) measure deficit as dividend plus investment and cashflow. Meanwhile, investment measured as capital expenditure and working capital to capture a firm s demand for funds due to its real investments. Bulan and Yan (2009) measure deficit as the financing deficit in period t scaled by total assets at the beginning of period t, financing deficit as net equity plus net debt issues, and capital expenditures as capital 82

83 expenditures divided by total assets. Frank and Goyal (2007) measure the deficit as cash dividends plus investments plus change in working capital minus internal cash flow. Sogorb-Mira and López-Gracia measured the financing deficit would be as Fixed current investment as the sum of capital expenditures, increase in investments, acquisitions, and other use of funds, less sale of plant, property, and equpment and sale of investment. Cash flow defined as cash flow after interest and taxes net of dividends, respectively. Financing Deficit = DIV + CAPEX + LTD payment + Δ WC CF in which DIV is dividend payments, CAPEX is capital expenditures, ΔWC is the net change in working capital, and CF is operating cash flow (after interest and taxes), long-term debt payment. All variables are scaled by total assets, as in Frank and Goyal (2003). B. Net Debt Issue Leary and Roberts (2005) measure debt issuances as a change in total debt (long term plus short term) divided by total assets in an excess of 5%. Frank and Goyal (2007) net debt issued as long-term debt issuance minus long-term debt redemption. Bulan and Yan (2009) measure net debt issued scaled by total assets, or net debt [long-term debt issuance minus long-term debt reduction divided by total assets. Net debt issue = (dta/ta) - (Net equity issue) (dre/ta) Where TA is total asset, dta is change in total asset, and dre is change in retained earning. C. Net Equity Issue Leary and Roberts (2005) measured equity issuances for year t as sale of common and preferred stock net of purchase of common and preferred stock. Frank and Goyal (2007) measured net equity issued as the issue of stock minus the repurchase of stock. Bulan and Yan (2009) measured net equity as sale of common and preferred stock minus purchase of common and preferred stock divided by total assets.. Net equity issue = (deq/ta) - (dre/ta), and NRE = dre/ta Where TA is total asset, deq is change in book equity, NRE is newly retained earning, and dre is change in retained earning Hypotheses Testing We have tested hypotheses 1-4 using regression. We used this statistical technique as we explored linear relationships between the predictor and criterion variables. The criterion variable and the predictor variable we used for making a prediction should be measured on a continuous scale (ratio scale). We also tested H2 by using an augmented model. 83

84 Hypothesis 1 The objective of testing hypothesis 1 is to examine the influence of growth opportunity, profitability, risk, size, and asset tangibility on short-term leverage, long-term leverage, total leverage, and market leverage. The regression equation for hypotheses 1a, 1b, 1c, 1d, 1e, 1f, is as follows: Y = a + β 1 * X 1 + β 2 * X 2 + β 3 * X 3 + β 4 * X 4 + β 5 * X 5 + e Where: Y = is the value of the dependent variable, Debt ratio a = is the intercept of the regression line on the Y axis when X= 0 β X 1 X 2 X 3 X 4 X 5 = is the slope of the regression line = Growth opportunity = Profitability = Risk = Size = Asset tangibility Hypothesis 2 The objective of testing hypothesis 2 is to examine how firms in the manufacturing sector raise capital for investments externally (with debt, equity, or debt to repurchase equity). Hypothesis 2 was analysed by using the mixed method approach. A. Quantitative Analysis For testing hypothesis 2, the independent variable was financing deficit, and net debt issue, net equity issue, and net debt issue to repurchase equity were the dependent variables. Therefore, the steps to analyse the relationship between variables are as follows: A.1. Measuring the Financing Deficit/Surplus The financing deficit would be approximated as: FINANCING DEFICIT = DIV + CAPEX + ΔWC + LTD payment CF In which DIV is dividend payments, CAPEX is capital expenditures, ΔWC is the net change in working capital, and CF is operating cash flow (after interest and taxes), LTD payment is longterm debt payment. All variables are scaled by total assets, as in Frank and Goyal (2003). A positive value of financing deficit indicates a financing deficit and a negative one indicates financing surplus. The financing deficit/surplus in equation is equivalent to the one used in previous studies. 84

85 A.2. Testing the Pecking Order Theory In Bulan and Yan (2007), the pecking order theory of Myers and Majluf (1984) and Myers (1984)) and its extensions (Lucas and McDonald (1990)) is based on the idea of asymmetric information between managers and investors. Managers know more about the true value of the firm and the firm s riskiness than less informed outside investors. If the information asymmetry causes the underpricing of the firm s equity and the firm is required to finance a new project by issuing equity, the underpricing may be so severe that new investors accept the largest part of the net present value of the project, resulting in a net loss to existing shareholders. Thus, managers who work in the greatest interest of the current shareholders will reject the project. To avoid the underinvestment problem, managers will search for financing the new project using a security that is not undervalued in the market, such as internal funds. Consequently, this affects the choice between internal and external financing. The pecking order theory is capable to explain why firms tend to depend on internal sources of funds and prefer debt to equity if external financing is required. Thus, a firm s leverage is simply the cumulative results of the firm s attempts to mitigate information asymmetry. Due to the valuation discount that less-informed investors apply to newly issued securities, so firms choose internal funds first, then debt and equity last to satisfy their financing needs (Bulan and Yan, 2007). In this section, we implement a test of the pecking order theory proposed by Shyam- Sunder and Myers (1999) given by the following: Net Debt Issue = a + b1 * Deficit + ε Where net debt issued and financing deficit, i.e. uses of funds minus internal sources of funds, (both scaled by total assets). This deficit is financed with debt and/or equity. If firms are consistent with the pecking order, changes in debt should track changes in the deficit one-for-one. Hence, the expected coefficient on the deficit is 1. Frank and Goyal (2003) showed that this test performed poorly for small firms and performed best for large firms. However, since small firms were thought to suffer most from asymmetric information problems, hence they should be the ones following the pecking order. A.3. Testing the Pecking Order and Debt Capacity with an Augmented Model In Laarni Bulan Zhipeng Yan (2007, as an alternative means of accounting for a firm s debt capacity, Lemmon and Zender (2007) and Agca and Mozumdar (2004) augmented equation with the deficit-squared: Net Debt Issue = a + b1 * Deficit + b2 * Deficit 2 + ε To estimate equation, we follow Bulan and Yan (2009). Firms that in accordance with the pecking order more strongly should have a debt-deficit sensitivity that is closer to one. The quadratic specification was used to account for requiring debt capacity constraints. This deficit is financed with debt and/or equity. If firms follow the pecking order, variations in debt should follow changes in the deficit one-for-one (Shyam-Sunder and Myers, 1999). If firms are financing their deficit with debt first and issue equity only when they achieve their debt capacities, then net debt issued is a concave function of the deficit (Chirinko and Singha, 2000) and the coefficient on the squared deficit term would be negative. The larger the deficit, the more probably it is for a firm to attain its debt capacity. In these instances, the debt-deficit sensitivity should be lower. A negative coefficient on the squared deficit term implies that firms are limited by their debt capacity inadequacy and they have to choice to issuing equity. A squared deficit coefficient that is large in 85

86 absolute value describes a greater reliance on equity finance for larger values of the financing deficit. If firms are issuing equity first and debt is the residual source of financing, then this relationship should be convex and the coefficient on the squared deficit term would be positive. If debt and equity are issued in static proportions, the deficit would have no influence on net debt issued. B. Qualitative Analysis To make sure that our regression result is robust, we also analyse the results qualitatively by using graphics and table analysis Hypothesis 3 The objective of testing H3 is to test the effect of issuing net debt, issuing net equity, and issuing net debt to repurchase equity, on the firm s stock price. The regression equation for hypothesis 3a, 3b, and 3c are as follow: Where: Y1 = a + β 1 * X 1 + e Y2 = a + β 2 * X 2 + e Y3 = a + β 3 * X 3 + e Y X 1 X 2 X 3 = stock price = net debt issue = net equity issue = debt issue to repurchase equity a = is the intercept of the regression line on the Y axis when X=0 β = is the slope of the regression line Hypothesis 4 The objective of testing hypothesis 4 is to examine the firm s capital structure over the life cycle of the firm to solve the problem of firm financing deficit. In testing the hypothesis, we first classified firms into two cohorts according to their life cycle stage, namely, firms in their growth stage and firms in their mature stage. Then we classified firms into small firms and large firms, and additionally young firms and old firms. Since we would like to examine how growth-mature firms and small-large firms finance their deficit, hence, it is important to make sub distinctions in the theoretical framework between growth-mature firms and small-large firms. Maturity and size can be regarded as a proxy for information asymmetry between firm insiders and the capital markets. Mature [large] firms are more closely observed by analysts and should therefore be more capable of issuing more equity, and have lower debt (e.g., their reputation in debt markets or the extent their assets are diversified). Growth [small] firms are on the other hand. Therefore, it is important to make sub distinctions in the theoretical framework between growth-mature firms and small-large firms. 86

87 In the context of a firm s life cycle, we expected that asymmetric information problems were more severe among growth [small] firms compared to firms that have reached maturity. Hence, the theory predicts that fast-growing [smaller] firms should be following the pecking order more closely. Life Cycle Definition Bulan and Yan (2009) defined the growth stage as the first six-year period after the year of the firm s initial public offering (IPO). This definition may not necessarily apply to some firms from a mechanical point of view. However, the IPO itself is an important financing decision that a firm has to make. Here, Bulan and Yan (2009) treated the IPO as the starting point of the growth stage (or the new growth stage). DeAngelo, DeAngelo and Stulz (2006), among others, found that a firm s propensity to pay dividends was a function of the stage where the firm is in its life cycle. In particular, Bulan, Subramanian and Tanlu (2007) found that dividend initiators were mature firms. Based on this body of work, they identified firms in their mature stage by their dividend initiation history. First, they used the entire compustat industrial annual database to find consecutive six-year periods for which a firm has positive dividends. They required that such a period should immediately follow at least one year with zero or missing dividends. They considered these 6-year dividend payment periods as the mature stage of a firm s life cycle. 1. Growth Firms and Mature Firms We took Grullon, Michaely and Swaminathan (2000), DeAngelo, DeAngelo and Stulz (2005) and Bulan, Subramanian and Tanlu as the references (2007) who found that firms initiated dividends were mature firms. Thus, we identified firms in their mature stage by their dividend history. Halov and Heider (2005), Leary and Roberts (2006) and Byoun (2007) showed that firm financing choice was complex and was driven by many factors which included both pecking order and trade-off theory considerations. We constructed two samples of firms according to their life cycle stage: firms in their growth stage and firms in their mature stage. Bulan and Yan (2007) set the length of each stage to be 6 years. Evans (1987) defined six years old or younger as young firms and seven years or older as old firms. We followed Bulan and Yan (2007) to set the length of each stage to be 6 years. Growth Stage Our sample was constructed from the manufacturing sector of the LQ45 index over the period. Some previous research defined the growth stage to be the first six-year period after the year of the firm s IPO, however we defined the growth stage to be the firms that paid dividend less then 5 years sequencialy. Mature Stage Bulan, Subramanian and Tanlu (2007) found that firms initiated dividends are mature firms. Thus Bulan and Yan (2007) identified firms in their mature stage by their dividend history. We took Bulan and Yan (2007) as a reference to construct the sample as follows: we included the former 6-year period in our sample. This 10-year requirement was to ensure that whatever reason for the dividend omission, the firm had fully recovered and re-emerged as a regular dividend payer. We consider these 6-year dividends payment periods as the mature stage of a firm s life 87

88 cycle. We found that 10 firms had one 6-year dividend payment period; while 16 firms had less than one 6-year dividend payment periods among the 26 firms. Table 5.2. Growth Firms No. Firm Life Cycle 1 ADMG Growth 2 BRPT Growth 3 BUDI Growth 4 CPIN Growth 5 DNKS Growth 6 FASW Growth 7 GJTL Growth 8 INDR Growth 9 INKP Growth 10 INAF Growth 11 INTP Growth 12 KOMI Growth 13 SMCB Growth 14 TKIM Growth 15 TSPC Growth 16 SULI Growth Table 5.3. Mature Firms No. Firm Life Cycle 1 ASII Mature 2 AUTO Mature 3 GGRM Mature 4 HMSP Mature 5 INDF Mature 6 KAEF Mature 7 KLBF Mature 8 RMBA Mature 9 SMGR Mature 10 UNVR Mature 88

89 2. Small Firms and Large Firms In Hufft, JR. study defined small as firms with less than 500 employees, total assets of less than $150 million, and annual sales of less than $20 million. Then we adopted it to define large firms that have total asset of more than $150 millions (equals to IDR 1,083, million). Table 5.4. Small Firms Firms USD 150 million (equals to IDR 1,083, million) Total Asset<$150 millions BUDI 496, Small DNKS 377, Small INAF 549, Small KOMI 323, Small KAEF 914, Small RMBA 946, Small TSPC 1,056, Small Table 5.5 Large Firms Firms USD 150 million (equals to IDR 1,083, million) ASII 30,934, Large ADMG 6,191, Large AUTO 1,347, Large BRPT 4,107, Large CPIN 1,995, Large FASW 1,811, Large GGRM 10,846, Large GJTL 9,353, Large HMSP 5,418, Large INDF 11,630, Large INDR 3,472, Large INKP 38,541, Large INTP 6,510, Large KLBF 2,564, Large SMCB 6,335, Large SMGR 5,729, Large SULI 1,401, Large TKIM 14,313, Large UNVR 2,996, Large Total Asset > USD 150 millions 89

90 3. Young Firms and Old Firms Evans (1987) defined six years old firms or younger as young firms and seven years firms or older as old firms. We followed this study and set the length of each stage to be 7 years (however, this restriction is not true for some firms from a manufacturing point of view). To take an example, KAEF was founded in 1969 and went public also in This firm is old enough and is mature in many respects. However, the IPO itself is an important financing decision that a firm has to make, and in many cases, indicates a significant change in the firm s development over its life cycle. Here, we treated the IPO as an important turning point in a firm s history and as the starting point of the old/young stage. Table showed that INAF and KAEF are 6 years from listing date to 2007 as our sampling period from 1994 to Table 5.6. Young and Old Firms Established Listed How Old Listed in IDX (no. of years from listed to 2007) ASII 20 Feb Apr AUTO 04 Apr Okt ADMG 25-Apr Oct BRPT 04-Apr Oct BUDI 15-Jan May CPIN 07 Jan Mar DNKS 25-Mar FASW 13-Jun Dec GGRM 26-Jun Aug GJTL 24-Aug May HMSP 27-Mar Aug INDF 14-Aug Jul INDR 03-Apr Aug INKP 07-Dec Jul INAF 02-Jan Apr INTP 16 Jan Des KLBF 10-Sep Jul KOMI 13-Dec Oct KAEF 23-Jan Jul RMBA 19-Jan Mar SMCB 15-Jun Aug SMGR 25-Mar Jul TKIM 02-Oct Apr TSPC 20-May Jun UNVR 05-Dec Jan SULI 14-Apr Mar

91 As the equations applied in hypothesis 2, we also tested hypothesis 4 by following a test of the pecking order theory proposed by Shyam-Sunder and Myers (1999) over the life cycle of the firm Regression Analysis Our regression analysis consists of the un-standardised Beta coefficients, the standardised Beta coefficients, analysis of variance (ANOVA), coefficients of determination (R 2 ), descriptive statistics, and regression assumptions of hypotheses 1-4. A. The Un-standardised Beta Coefficients The Un-standardised Beta Coefficients (B) is the value for the regression equation for predicting the dependent variable from the independent variable. These are called un-standardised coefficients because they are measured in their natural units. As such, the coefficients cannot be compared with one another to determine which one is more influential in the model, because they can be measured on different scales. B. The Standardised Beta Coefficients The Standardised Beta coefficients give a measure of the contribution of each variable to the model. A large value indicates that a unit change in this predictor variable has a large effect on the criterion variable. The t and sig (p) values give a rough indication of the impact of each predictor variable a big absolute t value and small p value suggests that a predictor variable is having a large impact on the criterion variable. When we have only one predictor variable in our model, then beta is equivalent to the correlation coefficient between the predictor and the criterion variable. This equivalence makes sense, as this situation is a correlation between two variables. C. Analysis of Variance (ANOVA) Analysis of variance enables an extrapolation of the t test results of two groups to three or more groups. The F-statistic will be calculated for analysis of variance (ANOVA) to test whether group population means are all equal or not. When the F-statistic is found significant, we may conclude that at least one of the population means of the groups differs from the others, but ANOVA does not tell us which groups are different from which. If this is the case, a multiplecomparison analysis by pairwise group comparison will be an appropriate answer to this question (Bekiro, 2001). The statistical significance as depicted in the ANOVA analysis of the models for firms reach statistical significance at significance value of p<0.05 (Coakes and Steed, 2003; and Pallant, 2005). D. The Coefficient of Determination (R 2 ) The multiple correlation coefficients (R) are the linear correlation between the modelpredicted and the observed values of the dependent variable. The coefficient of determination, or simply R-squared, has its value always between 0 and 1, and is interpreted as the percentage of variation of the response variables explained by the regression line. If there is no linear relation between the dependent and independent variable, R 2 is 0 or very small. If all the observations fall on the regression line, R 2 is 1. This measure of the goodness of fit of a linear model is also called the coefficient of determination. The sample estimate of R 2 tends to be an optimistic estimate of 91

92 the population value. Adjusted R Square is designed to more closely reflect how well the model fits the population and is usually of interest for models with more than one predictor. A high value of R 2, suggesting that the regression model explains the variation in the dependent variable well, is obviously important if one wishes to use the model for predictive or forecasting purposes. To be sure, a large unexplained variation in the dependent variable will increase the standard error of the coefficients in the model (which are a function of the estimated variance of the noise term), and hence regressions with low values of R 2 will often (but by no means always) yield parameter estimates with small t-statistics for any null hypothesis. Because this consequence of a low R 2 will be reflected in the t-statistics, however, it does not afford any reason to be concerned about a low R 2 per se. R Square (R 2 ) is the square of the measure of correlation and indicates the proportion of the variance in the criterion variable which is accounted for by our model. E. Descriptive Statistics Descriptive statistics describe the value of each variable including mean, minimum, and maximum values. F. Regression Assumptions of Hypothesis 1-4 Before analyzing regression coefficients of variables, we must first make several assumptions about the population of the research. They represent an idealisation of reality, and as such, they are never likely to be entirely satisfied for the population in any real study (Van Horne, 1998). A good regression model should not have the following assumptions: 1. Multicollinearity Multicollinearity implies that for some set of explanatory variables, there is an exact linear relationship in the population between the means of the response variable and the values of the explanatory variables (Van Horne, 1998). The goal of the multicollinearity test is to analyse whether there is correlation between independent variables. Multicollinearity in the regression model can be detected such as by testing the R 2 value and/or analysing the correlation matrix (Ghozali, 2002). The other ways to detect the problem of multicollinearity are the tolerance values and VIF (Hair et al., 1998). Correlations between Variables For correlations between variables, we do not want strong correlations between the criterion and the predictor variables. The Tolerance and VIF The tolerance values are a measure of the correlation between the predictor variables and can vary between 0 and 1. The closer to zero the tolerance value is for a variable, the stronger the relationship between this and the other predictor variables. We should worry about variables that have a very low tolerance (Van Horne, 1998). SPSS will not include a predictor variable in a model if it has a tolerance of less that However, we may want to set your own criteria rather higher perhaps excluding any variable that has a tolerance level of less than Meanwhile, VIF is an alternative measure of collinearity (in fact it is the reciprocal of tolerance) in which a large value indicates a strong relationship between predictor variables. 92

93 2. Autocorrelation Autocorrelation requires probabilistic independence of the errors. This assumption means that information on some of the errors provides no information on other errors. For time series data this assumption is often violated. This is because of a property called autocorrelation (Van Horne, 1998). Test of autocorrelation aims to examine whether in a linear regression model has correlation between trouble errors in the period t with an error in the period t-1 (before). One of the methods that can be used to detect autocorrelation is the Durbin Watson (DW). DW value shows that there is no autocorrelation in regression model. Durbin Watson (DW) Test Statistic In Field (2008), Durbin Watson test statistic, a test for correlation between errors. Specifically, it tests whether adjacent residuals are correlated. In short, this option is important for testing whether the assumption of independent errors is tenable. The test statistic can vary between 0 and 4 with a value of 2 meaning that the residuals are uncorrelated. A value greater than 2 indicates a negative correlation between adjacent residuals whereas a value below 2 indicates a positive correlation. The size of the DW statistic depends upon the number of predictors in the model, and the number of observations. As a conservative rule of thumb, Field (2009) suggested that, values less than 1 or greater than 3 gave definitely cause for concern, however values closer to 2 may still be problematic depending on the sample and model. 3. Heteroscedasticity This assumption concerns variation around the population regression line. Specifically, it states that the variation of the Y s about the regression line is the same, regardless of the value of the X s (Van Horne, 1998). Test of heteroscedasticity aims to interpret whether the regression model has the differences residual variance from one observation to another observation (Ghozali, 2002). If the residual variance from one observation to another observation is the same, it is called homoscedasticity. The graphic of scatterplot (in appendix) shows that the dots have not established a specific pattern. Some of the dots located adjacent but some other dots spread above and below the numbers of 0 at the axis Y. Thus, the data in the graphics exhibits homoscedasticity. 4. Normally Distributed The assumption states that the errors are normally distributed. We can check this by forming a histogram of the residuals. If the assumption holds, then the histogram should be approximately symmetric and bell-shaped. But if there is an obvious skewness, too many residual more than, say, two standard deviations from the mean, or some other non-normal property, then this indicates a violation of the assumption (Van Horne, 1998). From the graphics of histogram and normal P-P plot (in appendix), we concluded that the histogram gave the normal pattern of distribution. Meanwhile, the graphic of normal P-P plot shows that the dots spread around the diagonal line, and the spreading follows the diagonal line. Both graphics show that the data meets reasonable assumption of normality. 93

94 Based on the results of assumptions of population described above, the regression model does not have the assumptions of heteroscedasticity, multicollinearity, autocorrelation, and the data are normally distributed. Thus, our regression model is appropriate to use for testing the hypothesis The Credibility of Research Findings Underpinning the above discussion on multi-method usage has been the issue of the credibility of research findings. This is neatly expressed by Raimond (1993) and Rogers (1961, cited by Raimond, 1993). Reducing the probability of getting the answer wrong means that concentration has to paid to two particular emphases on research design, namely, reliability and validity Reliability Reliability examines whether the measurement can be repeated; that is, whether we are measuring something that can be replicated over time instead of a random effect. Reliability can be evaluated by using the following three questions (Easterby-Smith et al., 2002): 1. Will the measures yield the same results on other occasions? 2. Will similar observations be reached by other observers? 3. Is there transparency in how sense was made from the raw data? To ensure that this research has answered these three questions, we have reviewed the previous research findings concluded by other researchers from many research setting and time period Validity Validity is concerned with whether the findings are really about what they illustrate to be about. Is the relationship between two variables a causal relationship? We minimised the potential lack of validity in the conclusions by analysing the results obtained quantitatively and qualitatively. Even though analysing results obtained quantitatively and qualitatively does not minimise the potential lack of validity, the results obtained should be consistent with each other Generalisability Generalisability is sometimes referred to as external validity. A concern we may have in the design of our research is the extent to which your research results are generalisable: that is, whether our findings may be equally applicable to other research settings, such as other organisations. In this research, the purpose of our research will not be to produce a theory that is generalisable to all populations. Our objective will be simply to try to explain what is happened in Indonesia Capital Market. Therefore, our results can not be generalised The Limitations of Research Design There is no research project without limitations; and there is no research as a perfectly designed study. It is in line with Patton (1990), who noted that there are no perfect research designs and there are always trade-offs. Yin (2003) also noted that limitations derived from the conceptual framework and the study s design. Furthermore, each method, tool or technique has its unique strengths and weaknesses (Smith, 1975). 94

95 Since all different methods will have different effects, it makes sense if we use different methods to avoid the method effect. It will lead us to greater confidence being placed in our conclusions. Therefore, it is quite usual for a single study to combine quantitative and qualitative methods and/or to use primary and secondary data. There are two major advantages to employ multi-methods in the same study. First, different methods can be used for different purpose in a study. The second advantage of applying multi-methods is that it enables triangulation to take place. Triangulation refers to the use of different data collections methods within one study in order to ensure that the data are telling us what we believe they are describing us. In our research, we had two limitations as follow, the first is regarding to the limitation of data, as sometimes the data are not complete. The second is regarding to the data analysis. Therefore, we used regression and augmented equations and also qualitative analysis to explain the finding of hypotheses. 95

96 6. PRESENTATION OF DATA AND ANALYSIS OF RESULTS 6.1 Research Question 1, Hypotheses, Hypotheses Testing, and Result Analysis Chapter 6 described the hypothesis testing for research questions one and two, three, and four, and discussed the results obtained in detail. The chapter discussed the results for each research question. In chapter 1, four research questions were introduced. A total of 4 major hypotheses were constructed to assist in answering the research questions. Chapters 6 now discuss the findings from this inquiry. It presented and discussed the results of testing hypotheses 1, 2, 3, and 4 that belonged to research question one, two, three, and four respectively. The remaining research questions, the associated hypotheses and the results are presented below Research Question 1 In this research, our minor research questions are as follow: What are the determinants of capital structure of the firms in the manufacturing sector in Indonesia? a. As implied by the trade-off theory and the pecking order theory, do growth opportunities have a positive relationship with debt ratio? b. As the pecking order hypothesis, does a firm s profitability have a negative relationship with level of debt? And as implied by the trade-off theory, does a firm s profitability have a positive relationship with the debt ratio? c. In accordance with the pecking order theory and trade-off theory, is there a negative relationship between risk (earnings volatility) and debt ratio? d. As suggested by the trade-off theory, does size has a positive relationship with debt ratio? And as suggested by the pecking order theory of the capital structure, is there a negative relationship between level of debt and size of the firm? e. In accordance with the trade-off theory, is there a positive relationship between asset tangibility and level of debt? Hypothesis One (H1) In this research, our minor hypotheses one (H1) are as follow: H1.a: As implied by the trade-off theory and the pecking order theory, we hypothesise that growth opportunity is positively related to debt ratios. H1.b: As the pecking order hypothesis, we hypothesise that profitability has a negative relationship with debt ratios and based on the trade-off theory we hypothesise that profitability has a positive relationship with debt ratio. 96

97 H1.c: In accordance with the pecking order theory and trade-off theory, we hypothesise a negative relationship between risk (earnings volatility) and debt ratio. H1.d: As suggested by the trade-off theory, we hypothesise that size has a positive relationship with debt ratio, and as suggested by the pecking order theory of the capital structure there is a negative relationship between debt ratio and size. H1.e: In accordance with the trade-off theory, we hypothesise a positive relationship between asset tangibility and debt ratio Testing the Hypothesis 1 As described in chapter 5, multiple regression analysis was selected to test hypothesis 1. Variables used at hypothesis 1 are growth; asset tangibility; risk; size; and profitability as the independent variables and short-term leverage; long-term leverage; total leverage; market leverage as the dependent variables. The objective of regression analysis are to examine the linear relationships between the predictor and criterion variables, to examine the influence of growth opportunity; profitability; risk; size; and asset tangibility on short-term leverage; long-term leverage; total leverage; market leverage Analysis of Results Analysis of results is consistent of result analysis of each variables and its consistency to theory and previous research, and also the Indonesian capital market condition regarding variables relationship and LQ45 Index Analysis of the Result and Its Consistency to Theory and Previous Research The following is the regression result of the effect of independent variable on dependent variable level of significant is the highest significant level which implies that dependent variable is significantly influenced by independent variable. Table 6.1a. Regression Results of Hypothesis Testing 1 Model Unstandar dised Coefficients B Standar dised Coefficients Beta 97 t Sig. Collineari ty Statistics Tolerance Collinea rity Statistics VIF STL (Consta nt) PRFT TANG SIZE RISK GROW F= (0.000); R-squared=0.332; Adjusted R-squared=0.314; N=196 LTL (Consta nt) PRFT TANG

98 SIZE RISK GROW F= (0.000); R-squared=0.288 ; Adjusted R-squared= 0.269; N=196 Table 6.1b. Regression Results of Hypothesis Testing 1 Model Unstandar dised Coefficients B Standar dised Coefficients Beta t Sig. Collineari ty Statistics Tolerance Collinea rity Statistics VIF TLV (Consta nt) PRFT TANG SIZE RISK GROW F=72.059; R-squared=0.655 ; Adjusted R-squared=0.646 ; N=196 MRL (Consta nt) PRFT TANG SIZE RISK GROW F= (0.000) ; R-squared=0.638 ; Adjusted R-squared=0.629 ; N=196 A.Growth on Leverage From table 6.1, we can analyse the influence of growth on short-term leverage, long-term leverage, total leverage, and market leverage. Growth and Short-term Leverage Growth has a positive significant regression coefficient on short-term leverage, with level of significance and t-values. This suggests that high growth firms are more likely to use shortterm leverage for financing their investments than low growth firms. Growth and Long-term Leverage Growth has a positive significant regression coefficient on long-term leverage, with level of significance and t-values. This suggests that high growth firms are more likely to use longterm leverage for financing their investments than low growth firms. Growth and Total Leverage 98

99 Growth has a positive significant regression coefficient on total leverage, with level of significance and t-values. This suggests that high growth firms are more likely to use total leverage for financing their investments than low growth firms. Growth and Market Leverage Growth has a negative significant regression coefficient on market leverage, with level of significance and t-values. This suggests that high growth firms are less likely to use market leverage for financing their investments than low growth firms. Our results showed that growth was positively related with short-term leverage, long-term leverage, and total leverage. It was consistent with the pecking order theory. According to the pecking order theory hypothesis, a firm will first use internally generated funds which may not be sufficient for a growth firm. And the next option for the growth firms is to use debt financing which implies that a growth firm will have a high leverage (Drobetz and Fix 2003). Applying pecking order arguments, growth firms place a greater demand on the internally generated funds of the firm. Consequentially, firms with relatively high growth will tend to issue securities less subject to information asymmetries, i.e. short-term debt. This should lead firms with relatively higher growth to having more leverage. Our results were consistent with what Sogorb-Mira and Lopez-Gracia (2003) said that there was a positive relation between growth and short-term leverage, long-term leverage, and total leverage. Sogorb-Mira and López-Gracia (2003) tested leverage predictions of the trade-off and pecking order models. They used panel data Spanish SMEs. Their result showed a positive and statistically significant impact between growth opportunities and firm leverage. This result is consistent with the Michaelas et al. (1999) argument, based on the idea that in SMEs the trade off between independence and financing availability is more pronounced and the major part of debt financing is short term. Pandey (2001) examined the determinants of capital structure of Malaysian companies and showed that growth variable had a positive significant influence on all types of book and market value debt ratios. This finding supported both trade-off and pecking order theories. On the other hand, according to Çağlayan and Şak (2010), market to book was found to have positive effect on book leverage. Positive sign of market to book was also along the lines of pecking order theory. Our results were in line with what agency costs / trade-off theory that the growth was negatively related with market leverage. Agency costs for growth firms are expected to be higher as these firms have more flexibility with regard to future investments. The reason is that bondholders fear that such firms may go for risky projects in future as they have more choice of selection between risky and safe investment opportunities. Deeming their investments at risk in future, bondholders will impose higher costs at lending to growth firms. Growth firms that are facing higher cost of debt will use less debt and more equity. Congruent with this, Titman and Wessels (1988), Barclay et al. (1995) and Rajan and Zingales (1995), all found a negative relationship between growth opportunities and leverage. Following the trade-off theory, for companies with growth opportunities, the use of debt is limited as in the case of bankruptcy, the value of growth opportunities will be close to zero, growth opportunities are particular case of intangible assets (Myers, 1984; Williamson, 1988 and Harris and Raviv, 1990). Firms with less growth prospects should use debt because it has a disciplinary role (Jensen, 1986; Stulz, 1990). Firms with growth opportunities may invest sub- 99

100 optimally, and therefore creditors will be more reluctant to lend for long horizons. This problem can be solved by short-term financing (Titman and Wessels, 1988) or by convertible bonds (Jensen and Meckling, 1976; Smith and Warner, 1979). According to agency costs, on the other hand, Myers (1977) argued that due to agency problems, firms invested in assets that might generate high growth opportunities in the future faced difficulties in borrowing against such assets. For this reason, we might now instead expect a negative relationship between growth and leverage. Some research found the negative result, such as Huang and Song (2002), concluded that the static trade-off model seemed better than the pecking order hypothesis in explaining the features of capital structure for Chinese listed companies. They used sales growth rate to measure the past growth experience and Tobin s Q to measure a firm s growth opportunity in the future. Their finding showed that firms with a high growth rate in the past tended to have higher leverage, while firms that had a good growth opportunity in the future (a higher Tobin s Q) tended to have lower leverage. Sbeiti (2010) found a negative relation between growth opportunities and leverage, it was consistent with the predictions of the agency theory that high growth firms used less debt, since they did not wish to be exposed to possible restrictions by lenders. However, variables such as market to book ratio reflected the capital market valuation of the firm, which in turn was affected by the conditions of the capital market. In the Shah and Khan (2007) study, growth variable was significant and was negatively related to leverage. As expected, this negative coefficient showed that growth firms did not use debt financing. Their results were in conformity with the result of Titman and Wessels (1988); Barclay, et al. (1995) and Rajan and Zingales (1995). The usual explanation was that growing firms had more options of choosing between safe and risky firms. In Gaud, Jani, Hoesli, and Bender (2003), the negative sign of growth confirmed the hypothesis that firms with growth opportunities were less levered. To analyse further this relationship, they observed a negative relationship between growth and leverage when market values were used, and a positive relation when leverage was measured with book values. B. Profitability on Leverage We can see from table 6.1 to imply the influence of profitability on short-term leverage, long-term leverage, total leverage, and market leverage. Profitability and Short-term Leverage Profitability has a negative significant regression coefficient on short-term leverage, with level of significance and t-values. This suggests that high profitability firms are less likely to use short-term leverage for financing their investments than firms with low profitability. High profitability firms in the manufacturing sector of the LQ45 Index are less likely to use shortterm leverage for financing their investments than low profitability firms. Profitability and Long-term Leverage Profitability has a negative significant regression coefficient on long-term leverage, with level of significance and t-values. This suggests that high profitability firms are less likely to use long-term leverage for financing their investments than firms with low profitability. 100

101 Profitability and Total Leverage Profitability has a negative significant regression coefficient on total leverage, with level of significance and t-values. This suggests that high profitability firms are less likely to use total leverage for financing their investments than firms with low profitability. Profitability and Market Leverage Profitability has a negative significant regression coefficient on market leverage, with level of significance and t-values. This suggests that high profitability firms are less likely to use market leverage for financing their investments than firms with low profitability. Profitability has negative correlation with short-term leverage, long-term leverage, total leverage, and market leverage. Comparing the results with the theory, all of our results are negative and they are in line with the pecking order theory but contradicting with the trade-off theory. The pecking order theory, based on works by Myers and Majluf (1984) suggests that firms have a pecking-order in the choice of financing their activities. Roughly, this theory states that firms prefer internal funds rather than external funds. If external finance is required, the first choice is to issue debt, then possibly with hybrid securities such as convertible bonds, then eventually equity as a last resort (Brealey and Myers, 1991). This behaviour may be due to the costs of issuing new equity, as a result of asymmetric information or transaction costs. All things being equal, the more profitable the firms are, the more internal financing they will have, and therefore we should expect a negative relationship between leverage and profitability. This relationship is one of the most systematic findings in the empirical literature (Harris and Raviv, 1991; Rajan and Zingales, 1995; Booth et al., 2001). There are conflicting theoretical predictions on the effects of profitability on leverage (Rajan and Zingales, 1995); while Myers and Majluf (1984) predicted a negative relationship according to the pecking order theory, Jensen (1986) predicted a positive relationship. Following the pecking order theory, profitable firms, which have access to retained profits, can use these for firm financing rather than accessing outside sources. However, in a trade-off theory framework, an opposite conclusion is expected. When firms are profitable, they should prefer debt to benefit from the tax shield. In addition, if past profitability is a good proxy for future profitability, profitable firms can borrow more as the likelihood of paying back the loans is greater. From the trade-off theory point of view more profitable firms are exposed to lower risks of bankruptcy and have greater incentive to employ debt to exploit interest tax shields. Hence, high profitability firms in the manufacturing sector of the LQ45 Index do not want to take benefit from the tax shield. Meanwhile, based on agency theory, there are two possible explanations. Jensen (1986) predicted a positive relationship between profitability and financial leverage, if the market for corporate control was effective, such relation occurred because debt reduced the free cash flow generated by profitability. However, if it was ineffective, Jensen (1986) predicted a negative relationship between profitability and leverage. Comparing the results with previous studies, they were consistent. Drobetz and Fix (2003) tested leverage predictions of the trade-off and pecking order models using Swiss data. Their results were in conformity with the pecking order model but contrary to the trade-off model, more profitable firms used less leverage. They found that profitability was negatively correlated 101

102 with leverage, both for book and market leverage. This result reliably supported the predictions of the pecking order theory. The Huang and Song (2002) study results were consistent with the predictions of theoretical studies and the results of previous empirical studies. Profitability was strongly negatively related with total liabilities ratios. The Pandey (2001) results showed that profitability had a significant inverse relation with all types of book and market value debt ratios. He showed that the results confirmed findings of earlier studies and were consistent with pecking order theory (Myers, 1984) that postulated a negative relationship between profitability and debt ratio. Cole (2008) showed a consistent negative relation between profitability with the loan-toasset ratio. The coefficients for return on asset were significant. These later findings were strongly supportive to the pecking order theory which predicted that profitable firms used less debt because they could fund projects with retained earnings. It was inconsistent with trade-off theory that predicted profitable firms used more debt to take advantage of the debt tax shield The other reason was they had lower probability of financial distress. Sbeiti (2010) found that firm profitability seemed to have a statistically negative and significant relationship with both the book and market leverage in the three countries. It was consistent with Booth et al. (2001), who reported the same results for the profitability variable and argued that the importance of profitability was related to the significant agency and informational asymmetry problems in developing countries. The results were also consistent with Titman and Wessels (1988), Rajan and Zingales (1995), Cornelli et al. (1996), Bevan and Danbolt (2002) in developed countries, Pandey (2001), Um (2001), Wiwattanakantang (1999), Chen (2004), Deesomsak, Paudyal and Pescetto (2004) and Antoniou et al. (2007). The Shah and Khan (2007) study found the negative sign and statistical significance. Frydenberg (2001b) described retained earning as the most important source of financing. Good profitability thus reduced the need for external debt. In Çağlayan and Şak (2010) study, profitability was found to have negative effect on the book leverage. A negative relationship between profitability and leverage was observed in the majority of empirical studies. This study provided similar results confirming the pecking order theory rather than static trade-off theory. In the Han-Suck Song (2005) study, profitability was negatively correlated with all three leverage measures, which was in line with the pecking-order theory. Firms preferred using surplus generated by profits to finance investments. This result might also indicate that firms in general always preferred internal funds rather than external funds, irrespective of the characteristic of an asset that should be financed (e.g. tangible or nontangible asset). Gaud, Jani, Hoesli and Bender (2003), reported in several other studies that the profitability variable was negative and significant in all cases (Rajan and Zingales, 1995; Booth et al., 2001; Frank and Goyal, 2002). This finding provides support for the pecking order theory. In Indonesia, previous empirical testing showed a significant negative relationship between profitability and leverage. This phenomenon indicates that the lower the profitability, the higher the leverage or vice versa. If the indication happens, it leads to a state that firm s debt to help increasing liquidity but it is not supported by the firm s performance. This indicates the occurrence of agency problems. If the opposite happens then the relationship is consistent with the pot which states that profitability is negatively related to leverage. In this case the firm is the low use of debt with high profitability. According to pecking order theory, high profitability firms borrow less because such firms have more internal financing, while firms with lower profitability require external funding and the consequence is debt accumulation (Sugiarto, 2009). 102

103 C. Risk on Leverage The following result is the analysis of the effect of risk on short-term leverage, long-term leverage, total leverage, and market leverage (table 6.1). Risk and Short-term Leverage Risk has a positive significant regression coefficient on short-term leverage, with level of significance and t-values. This suggests that high risk firms are more likely to use short-term leverage for financing their investments than low risk firms. Risk and Long-term Leverage Risk has a negative significant regression coefficient on long-term leverage, with level of significance and t-values. This suggests that high risk firms are less likely to use long-term leverage for financing their investments than low risk firms. Risk and Total Leverage Risk, has a positive significant regression coefficient on total leverage, with level of significance and t-values. This suggests that high risk firms are more likely to use total leverage for financing their investments than low risk firms. Risk and Market Leverage Risk has a positive but not significant regression coefficient on market leverage, with level of significance and t-values. This suggests that high risk firms are more likely to use market leverage for financing their investments than low risk firms. Our result showed that risk has positive influence on short-term leverage, total leverage, and market leverage, while it has negative effect on long-term leverage. The negative result supported both the trade-off theory that the more volatile cash flows the higher the probability of default and the pecking order theory that issuing equity is more costly for firms with high volatile cash flows. Our positive result supported the agency theory that the problem of underinvestment decreased when the volatility of the firms returns increased, hence, firms use more leverage. Bradley et al., (1984); Kester, (1986); Titman and Wessels (1988) found that since higher variability in earnings indicates that the probability of bankruptcy increases, they expect that firms with higher income variability have lower leverage. Firms that have high operating risk can lower the volatility of the net profit by reducing the level of debt. A negative relation between operating risk and leverage is also expected from a pecking order theory perspective: firms with high volatility of results try to accumulate cash during good years, to avoid under-investment issues in the future. Drobetz and Fix (2003) found as expected, the leverage was negatively related to the volatility. They also showed that their finding supported both the trade-off theory (more volatile cash flows increase the probability of default) and the pecking order theory (issuing equity is more costly for firms with volatile cash flows). Pandey (2001) found that there was a negative relation of earnings volatility with book and market value long-term debt ratio, which was consistent with the trade-off theory. It also revealed a positive relation between risk and short-term debt ratios. 103

104 We found that risk was positively related with the short-term leverage, and risk was also positively related with the total leverage and market leverage. Those were in line with the agency theory that Cools (1993) said it suggested positive relationship between earning volatility and leverage. He said that the problem of underinvestment decreased when the volatility of the firms return increased. The Huang and Song (2002) results showed that there was a positive relation between total liabilities ratio and volatility. It was consistent with Hsia s (1981) view that firms with a higher leverage level tended to make riskier investment. They found that the companies with high leverage in China tended to make riskier investments. D. Size on Leverage Table 6.1 indicates the regression result of the effect of size on short-term leverage, longterm leverage, total leverage, and market leverage. Our analysis is as follows: Size and Short-term Leverage Size has a positive but not significant regression coefficient on short-term leverage, with level of significance and t-values. This suggests that larger firms are more likely to use short-term leverage for financing their investments than small size firms. Size and Long-term Leverage Size has a negative but not significant regression coefficient on long-term leverage, with level of significance and t-values. This suggests that larger size firms are less likely to use long-term leverage for financing their investments than small size firms. Size and Total Leverage Size has a positive but not significant regression coefficient on total leverage, with level of significance and t-values. This suggests that larger size firms are more likely to use total leverage for financing their investments than small size firms. Size and Market Leverage Size has a negative significant regression coefficient on market leverage, with level of significance and t-values. This suggests that larger size firms are less likely to use market leverage for financing their investments than small size firms. Our results which describe that the size was positively related with total leverage and short-term leverage were consistent with trade-off theory, meanwhile our results which show that the size was negatively related with market leverage and long-term leverage were consistent with pecking order theory. Rajan and Zingales (1995) argued that there was less asymmetrical information about the larger firms. This reduced the chances of undervaluation of the new equity issue and thus encouraged the large firms to use equity financing. Static trade-off theory is generally interpreted as predicting that large firms will have more debt since larger firms are more diversified and have lower default risk. Larger firms are also typically more mature firms. These firms have a reputation in debt markets and consequently face lower agency costs of debt. Hence, the trade-off theory predicts that leverage and firm size should be positively related. The pecking order theory is usually interpreted as predicting an inverse 104

105 relation between leverage and firm size. The argument is that large firms have been around longer and are better known. Thus, large firms face lower adverse selection and can more easily issue equity compared to small firms where adverse selection problems are severe. Large firms also have more assets and thus the adverse selection may be more important if it impinges on a larger base. There are several theoretical reasons why firm size is related to the capital structure. Smaller firms may find it relatively more costly to resolve informational asymmetries with lenders and financiers, which discourages the use of outside financing (Chung, 1993; Grinblatt and Titman, 1998) and should increase the preference of smaller firms for equity relative to debt (Rajan and Zingales, 1995). However, this problem may be mitigated with the use of short term debt (Titman and Wessels, 1988). Relative bankruptcy costs and probability of bankruptcy (larger firms are more diversified and fail less often) are an inverse function of firm size (Warner, 1977; Ang et al., 1982; Pettit and Singer, 1985; Titman and Wessels, 1988). A further reason for smaller firms to have lower leverage ratios is that smaller firms are more likely to be liquidated when they are in financial distress (Ozkan, 1996). Some previous studies conclude positive relationship, for example Drobetz and Fix (2003) found that size was positively related to leverage, indicating that size was a proxy for a low probability of default. This is in contrast to the results in Rajan and Zingales (1995), where firms in Germany tend to be liquidated more easily than in the Anglo-Saxon countries. Large firms have substantially less debt than of small firms. Therefore, Drobetz and Fix (2003), concluded that this result supported the trade-off theory, suggesting that large firms showed lower probability of default. Sogorb-Mira and López-Gracia (2003) found that firm size and leverage were positively related. They explained that this relationship could come from the fact that SMEs had to face higher bankruptcy costs, greater agency costs and bigger costs to resolve the higher informational asymmetries. Even within this firm category, SMEs of greater size could access a higher leverage. Their result was also the same as that obtained by a considerable number of previous studies (Ocaña et al., 1994; Hutchinson, 1995; Chittenden et al., 1996; Berger and Udell, 1998; Michaelas et al., 1999; and Romano et al., 2000). Pandey (2001) showed that the positive correlation between size and debt ratios confirmed the hypothesis, that larger firms tended to be more diversified and less prone to bankruptcy and the direct cost of issuing debt or equity was smaller. This is consistent with the trade-off theory. Sbeiti (2010) investigated the determinants of capital structure in the context of three GCC countries and the impact of their stock markets' development on the financing choices of firms operating in these markets. He found that the coefficient values of the size variable remained positive and were statistically significant in relation to both book and market leverage ratios across the three countries. The result was in line with results reported by Rajan and Zingales (1995), Wiwattanakantang (1999), Booth et al. (2001), Pandey (2001), Prasad et al. (2001), Deesomsak, Paudyal and Pescetto (2004), and Antoniou et al. (2007), the size coefficient was positive and statistically significant in the case of all three countries and for both measures of leverage. In Shah and Khan (2007) study, size had a positive coefficient but was insignificant. The coefficient value was However, the t-value of 0.07 was very small and the p-value was This showed that size variable was not a proper explanatory variable of debt ratio. This finding did not confirm our second hypothesis. Our second hypothesis was based on the Rajan and 105

106 Zingales (1995) argument that there was less asymmetric information about the larger firms which reduced the chance of undervaluation of new equity. Our finding did not confirm the Titman and Wessels (1988) argument as well that larger firms were more diversified and had lesser chances of bankruptcy that should motivate the use of debt financing. Why did our finding on size of a firm with relation to the leverage ratio not confirm the established theories? Trade off theory suggested that firm size should matter in deciding an optimal capital structure because bankruptcy costs constituted a small percentage of the total firm value for larger firms and greater percentage of the total firm value for smaller firms. As debt increased the chances of bankruptcy, hence smaller firms should have lower debt ratio. Çağlayan and Şak (2010) showed size was found to have positive relationships with the leverage of banks in this study. The findings of the relationship with the size were in line with the static trade-off and agency cost theory. In the Han-Suck Song (2005) study, the results revealed that size was a significant determinant of leverage. But while size was positively related to both total debt and short-term debt ratio, it was negatively correlated with long-term debt ratio, although the economic significance was rather small for the latter case. Even if the data did not allow us to further decompose short-term debt, we might still find the results of Bevon and Danbolt (2000) interesting. They found that while size was positively correlated with both trade credit and equivalent and short-term securitized debt, it was negatively correlated with short-term bank borrowing. This may indicate that small firms were supply constrained, in that they did not have sufficient credit ranking to allow them to long-term borrowing. Gaud, Jani, Hoesli and Bender (2003) analysed the determinants of the capital structure Swiss companies listed in the Swiss stock exchange. They found the positive impact of size on leverage was consistent with the results of many empirical studies (Rajan and Zingales, 1995; Booth et al., 2001; Frank and Goyal, 2002). It led them to reject the hypothesis that size acted as an inverse proxy for informational asymmetries, but could suggest that size acted as an inverse proxy for the probability of bankruptcy. Some previous studies which had negative result for this relationship were as follows. Huang and Song (2002) concluded that, on the relationship between size and leverage, if size is interpreted as a reversed proxy for bankruptcy cost, it should have less or no effect on Chinese firms leverage because the state kept around 40% of the stocks of these firms and, because of soft budget constraint, state-controlled firms should have much less chance to go bankrupt. Cole (2008), stated that firm size, as measured by the natural logarithm of total assets, was inversely related to firm leverage, and this relation was significant better than the level in each survey. In other words, larger firms used significantly less debt in their capital structure. In Indonesia, firm size has positive regression coefficient on short-term and long-term liabilities. It indicates that larger firms tend to have more debt. Firm size is a proxy for information asymmetry between the firm and market. According to the pecking order theory, there will be a negative relationship between leverage and firm size. Because, the bigger the firm the greater the access to capital markets, so that firms will reduce their leverage and prefer to issue equity. Previous empirical finding in Indonesia showed that there was a negative relationship existing between firm size and leverage (in Sugiharto, 2009). E. Tangibility on Leverage Finally, table 6.1 implies the regression result of the influence of tangibility on short-term leverage, long-term leverage, total leverage, and market leverage. Our analysis is as follows: 106

107 Tangibility and Short-term Leverage Tangibility has a negative significant regression coefficient on short-term leverage, with level of significance and t-values. This suggests that high tangibility firms are less likely to use short-term leverage for financing their investments than firms with low tangibility. Tangibility and Long-term Leverage Tangibility has a positive significant regression coefficient on long-term leverage, with level of significance and t-values. This suggests that high tangibility firms are more likely to use long-term leverage for financing their investments than firms with low tangibility. Tangibility and Total Leverage Tangibility has a positive but not significant regression coefficient on total leverage, with level of significance and t-values. This suggests that high tangibility firms are more likely to use total leverage for financing their investments than firms with low tangibility. Tangibility and Market Leverage Tangibility has a positive significant regression coefficient on total leverage, with level of significance and t-values. This suggests that high tangibility firms are more likely to use market leverage for financing their investments than firms with low tangibility. Our results show that high tangibility firms in the manufacturing sector of the LQ45 Index use more long-term leverage, total leverage, and market leverage. However, high tangibility firms use less short-term leverage, it implies that short-term leverage needs less tangibility of assets. If we compare our results to the theory, that the tangibility is negatively related with shortterm leverage, it is in line with the agency cost theory. Based on the agency problems between managers and shareholders, Harris and Raviv (1990) suggested that firms with more tangible assets should take more debt. This is due to the behaviour of managers who refuse to liquidate the firm even when the liquidation value is higher than the value of the firm as a going concern. Indeed, by increasing the leverage, the probability of default will increase for the benefit of the shareholders. In an agency theory framework, debt can have another disciplinary role: by increasing the debt level, the free cash flow will decrease (Grossman and Hart, 1982; Jensen, 1986; Stulz, 1990). As opposed to the former, this disciplinary role of debt should mainly occur in firms with few tangible assets, because in such a case it is very difficult to monitor the excessive expenses of managers. Previous studies with negative correlation between variables are as follows. Huang and Song (2002) found that, in contrast to theoretical predictions, tangibility was negatively related with total liability. They explained that the reason for that might be the non-debt part of total liability did not need collaterals. Long-term debt ratio is positively correlated with tangibility. Pandey s results (2001) indicated a significant negative relation of tangibility with book and market value short-term debt ratios. The relation of tangibility with the market value longterm debt ratio was also significantly negative whilst with book value long-term ratio was not statistically significant. These results contradicted with the trade-off theory that postulated a positive correlation between long-term debt ratio and tangibility since fixed assets acted as collateral in debt issues. 107

108 Sbeiti (2010) found that the stylised fact that the tangibility variable was positively related to the availability of collateral and leverage was not consistent with the findings in the paper, where tangibility was negative and statistically significant in relation to both book and market value of leverage in the three countries. In general, this negative association between leverage and tangibility can be explained by the fact that those firms that maintain a large proportion of fixed assets in their total assets tend to use less debt than those which do not. This is due to the fact that a firm with an increasing level of tangible assets may have already found a stable source of income, which provides it with more internally generated funds and avoid using external financing. Another explanation for this relationship could be the view that firms with higher operating leverage (high fixed assets) would employ lower financial leverage. Overall the results are consistent with Cornelli et al. (1996), Hussain and Nivorozhkin (1997), Booth et al. (2001), Nivorozhkin (2002) who also suggested a negative relation between tangibility and debt ratio. Finally, the relatively larger coefficient value of tangibility for the Saudi firms may indicate that firms in this country have an effective guarantee against bankruptcy. Çağlayan and Şak (2010) found that the relationship between tangibility and book leverage was also found to be negative in this study. This significant negative relationship between tangibility and leverage provided further support for the agency cost theory and the existence of conflict between debt holders and shareholders. These results also confirmed with results of empirical studies for developing countries whereas studies for developed countries showed a positive relationship. Our results show that high tangibility firms use more long-term leverage, more total leverage, and more market leverage. These are in line with the pecking order theory and trade-off theory. According to the pecking order theory and the trade-off theory, a firm with a large amount of fixed asset can borrow at relatively lower rate of interest by providing the security of these assets to creditors. Having the incentive of getting debt at lower interest rate, a firm with a higher percentage of fixed asset is expected to borrow more than a firm which cost of borrowing is higher because of having less fixed assets. Thus, there is a positive relationship between tangibility of assets and leverage. From a pecking order theory perspective, firms with few tangible assets are more sensitive to informational asymmetries. These firms will thus issue debt rather than equity when they need external financing (Harris and Raviv, 1991), leading to an expected negative relation between the importance of intangible assets and leverage. Most empirical studies concluded to a positive relation between collaterals and the level of debt (Rajan and Zingales, 1995; Kremp et al., 1999; Frank and Goyal, 2002). Inconclusive results were reported for instance by Titman and Wessels (1988). Some previous studies which conclude positive relationship are as follows: Drobetz and Fix (2003), found that tangibility was almost always positively correlated with leverage. They showed that this supported the prediction of the trade-off theory that the debt-capacity increased with the proportion of tangible assets on the balance sheet. Rebel A. Cole (2008) found tangibility was positive across each of the four surveys and was statistically significant at better than the 0.05 level for each survey except for the year According to Frank and Goyal (2006), the relation between tangibility and leverage was reliably positive in cross-sectional studies of publicly traded firms. Shah and Khan (2007) found that tangibility, with coefficient of was significantly related to debt. Thus their hypothesis was confirmed by the statistically significant positive relationship between tangibility and leverage. This finding was in contrast to the earlier finding by Shah and Hijazi (2004). They found that tangibility was not significantly related to leverage ratio. 108

109 In the Han-Suck Song (2005) study, as can be seen, the coefficients of tangibility were highly statistically significant for all three debt measures. But while the results showed that tangibility had a positive relationship with the total debt ratio and the long-term debt ratio, as expected according to the theoretical discussion above, tangibility was negatively related to the short-term debt ratio. This finding was consistent with the results of Bevan and Danbolt (2000), Huchinson et al. (1999), Chittenden et al. (1996) and Van der Wijst and Thurik (1993) report (Michaleas et al., 1999). Indeed, this result supported the maturity matching principle: long-term debt forms were used to finance fixed (tangible) assets, while non-fixed assets were financed by short-term debt (Bevan and Danbolt, 2000). Gaud, Jani, Hoesli and Bender (2003) showed that the coefficient of the tangibility variable was positive and significant for the panel data estimations, and this result was similar to those reported in previous research (Rajan and Zingales, 1995; Kremp et al., 1999; Frank and Goyal, 2002). This result suggested that firms used tangible assets as collateral when negotiating borrowing, especially long term borrowing. The observed sign of the relationship did not confirm the sign that would be expected when using the pecking order theory framework. In such a framework, firms with less tangible assets are more subject to informational asymmetries, and are more likely to use debt principally short term debt when they need external financing. Relationship between tangibility, risk, and leverage in the context of Indonesia are as follows: Result showed that asset tangibility had negative regression coefficient on short-term liability while it had positive regression coefficient on long-term liability. It indicated that firms with higher tangible asset tended to have less short-term debt but had more long-term debt. This result was consistent with the finding which showed that firm s risk had positive regression coefficient on short-term liability while it had negative regression coefficient on long-term liability. It indicated that firms with higher risk of bankruptcy and low tangible asset tended to have more short-term debt but had less long-term debt. Chen and Hammes (2003) found that tangible assets positively related to leverage. Previous empirical findings in Indonesia found that the negative coefficient of tangible assets to leverage. This indicated the possibility that the larger proportion of tangible assets, the lower the leverage, or the lower the tangible asset the higher the leverage. The significant negative coefficient of tangible assets indicated giving debt to the firm without considering the firm tangible assets. Therefore, firms that have higher proportion of tangible assets can borrow more (Rajan and Zingales, 2005) Analysis of the Indonesian Condition Our findings are implied that high growth firms in the manufacturing sector of the LQ45 Index are more likely to use short-term leverage, long-term leverage, and total leverage for financing their investments than low growth firms. However, firms with relatively high growth use less market leverage. Market leverage and firm size have negative correlation and growth and firm size has positive correlation which shows that high growth firms use less market leverage as they are large firms. 16/26 of our samples are growth firms. Firms with relatively high growth will tend to issue securities less subject to information asymmetries, i.e. shot-term debt. Firms in the manufacturing sector of the LQ45 Index with relatively high growth are also use more long-term and total leverage as when they use long-term leverage and total leverage for financing their investments, they have asset tangibility to secure their long-term debt. It is shown by positive correlation between long-term leverage and total leverage and tangibility. Even though high growth firms will face more information asymmetries, the Indonesian capital market has already had the regulation to minimise information asymmetries, such as regulation of capital market supervisory agency financial institution, regarding disclosure of 109

110 information that must be announced to the public, and decision of the board of directors of Indonesia Stock Exchange, concerning the obligation to deliver information. For firms in the manufacturing sector of the LQ45 Index, financing constraints will be more easily solved, as they have more access to banking. Banks will be more recognised and trusted the companies. It is not excessive considering each moment banks can determine the condition of the company's financial through various disclosure of information which announced by the company in the Stock exchange. With this condition, not only the process of granting new loans will be easier, but also rate of interest charged may also be lower considering that the credit risk of public companies is relatively smaller. Firms also have easier access to the company to enter into money markets through the issuance of debt, both short and long term. Generally the buyer of a letter of debt would certainly prefer if the company which issues a letter of Debt has become a public company especially firms from LQ45 Index. High profitability firms in the manufacturing sector of the LQ45 Index are less likely to use short-term leverage, long-term leverage, total leverage, and market leverage for financing their investments than low profitability firms. Even though profitability has negative correlation with risk, which implies that high profitability firms in the manufacturing sector has low risk, firms prefer use more internal funds rather than more external funds. Comparing the results with the theory, all of our results are negative and they are in line with the pecking order theory, but contradicting the trade-off theory. Hence, high profitability firms in the manufacturing sector of the LQ45 Index use their retained earning and do not want to take benefit from the tax shield. Result showed that high risk firms in the manufacturing sector of the LQ45 Index have lower long-term leverage than low risk firms, and it was in line with the pecking order theory and trade-off theory. As long-term leverage needs more collateral to secure this leverage, the firms with high risk should have lower long-term leverage. The correlation table indicates that high risk firms have low profitability, low tangibility, and low size; hence, they use less long-term leverage. Earning volatility is proxy for the probability of financial distress and the firm will have to pay risk premium to outside fund providers. To reduce the cost of capital, a firm will first use internally generated funds and then outsider funds. This suggests that earning volatility is negatively related with leverage, especially long-term leverage. However, our results showed that high risk firms in the manufacturing sector use more short-term leverage, total leverage, and market leverage than low risk firms. In Indonesia, for firms in the manufacturing sector of the LQ45 Index, financing constraints will be more easily solved, and rate of interest charged may also be lower, considering that the credit risk of public companies is relatively smaller, and generally the buyer of a letter of debt would certainly prefer if the company is from the LQ45 Index. Our results showed a positive relation between firm size in the manufacturing sector of the LQ45 Index and short-term leverage, and between size and total leverage. These are consistent with the following theories: As trade-off theory states, first, large firms did not consider the direct bankruptcy costs as an active variable in deciding the level of leverage as these costs were fixed by constitution and constituted a smaller proportion of the total firm s value. And also, larger firms were more diversified and had lesser chances of bankruptcy. Meanwhile, small firms often suffer the problems associated with asymmetric information, such as adverse selection, and they have to face higher bankruptcy costs, greater agency costs and bigger costs to resolve the higher informational asymmetries. That is why there is a positive relationship between size and shortterm leverage and total leverage of our manufacturing firm. 110

111 Our results show that the size was negatively related to market leverage and long-term leverage and they were consistent with the pecking order theory. As Rajan and Zingales (1995) argued there was less asymmetrical information about the larger firms. This reduced the chances of undervaluation of the new equity issue and thus encouraged the large firms to use equity financing. Hence, larger firms in the manufacturing sector of the LQ45 Index have less long-term leverage and market leverage. Meanwhile, size positively related to total leverage and short-term leverage was consistent with trade-off theory. It implies that larger firms would take the tax shield benefit. Our results show that high tangibility firms in the manufacturing sector of the LQ45 Index use more long-term leverage, total leverage, and market leverage. According to the pecking order theory and trade-off theory, a firm with a large amount of fixed asset can borrow at a relatively lower rate of interest by providing the security of these assets to creditors. Having the incentive of getting debt at lower interest rate, a firm with a higher percentage of fixed assets is expected to borrow more as compared to a firm whose cost of borrowing is higher because of having less fixed assets. However, high tangibility firms in the manufacturing sector of the LQ45 Index use less short-term leverage; it implies that short-term leverage needs less tangibility of assets Research Question 2, Hypothesis 2, Hypothesis Testing, and Result Analysis In this sub-section, we will analyse hypothesis 2 with quantitative and qualitative analysis. The research question two, hypothesis two, hypothesis testing, and the result of the analysis are as follow: Research Question 2 In this research, our research question two is as follows: How do firms in the manufacturing sector in Indonesia raise capital for investments, internally or externally (with debt, equity, or debt to repurchase equity)? Hypothesis 2 Based on research question two, our hypothesis two (H2) is as follows: Firms in the manufacturing sector in Indonesia raise capital for investments externally (with debt, equity, or debt to repurchase equity) Testing the Hypothesis 2 As described in the chapter on research methodology, for testing hypothesis 2, with the independent variable as financing deficit, and net debt issue, net equity issue, and issue debt to repurchase equity as the dependent variables, we apply multiple regression analysis and augmented analysis to test hypothesis 2. The objective of regression analysis is to examine which firm is following the pecking order theory more, growth firms or mature firms. If the firms follow the pecking order, the deficit is financed with internal financing, if they use the external financing, the financing deficit is financed with debt first, then equity. The firms which follow the pecking order have the changes in debt with track changes in the deficit one-for-one. Hence, the expected coefficient on the deficit is 1. The objective of augmented analysis is to examine how growth and mature firms finance the deficit, with debt first or equity first. If the firms follow the pecking order, changes in debt 111

112 should track changes in the deficit one-for-one (Shyam-Sunder and Myers, 1999). If firms are financing their deficit with debt first and issue equity only when they reach their debt capacities, then net debt issued is a concave function of the deficit. (Chirinko and Singha, 2000) and the coefficient on the squared deficit term would be negative. If firms are issuing equity first and debt is the next source of financing, then this relationship should be convex and the coefficient on the squared deficit term would be positive Analysis of Quantitative Results of Hypothesis 2 Analysis of results for hypothesis 2 is consists of quantitative and qualitative analysis. Our quantitative analysis is about variables relationship and its consistency to theory and previous research, and also about the Indonesia capital market condition Analysis of Results and Its Consistency to the Theory and Previous Research The results of hypothesis testing 2 of the influence of financing deficit on net debt issue and net equity issue are as follow. It includes analysis of regression and augmented model result. Table 6.2 Regression Results of Hypothesis Testing 2 (Net Debt and Net Equity Issue) Coefficients Model Unstandar dised Coefficients Standardi sed Coefficients t Sig. Collinearity Statistics B Std. Beta Tolera VIF Error nce NDEBT (Cons tant) FD F= (0.000) ; R-squared=0.600; N=53 NEQUITY (Cons tant) FD F= (0.000) ; R-squared=0.215 ; N=53 NRE (Cons tant) FD F=3.010 (0.089) ; R-squared=0.056 ; N=53 Table 6.3 Augmented Model Results of Hypothesis Testing 2 Coefficients Model Unstandar Standar dised Coefficientefficients dised Co- B Std. Beta Error NDEBT (Consta t Sig. Collinearity Statistics Tolera nce VIF

113 nt) FD FDSQR Independent Variable: FD F= (0.000) ; R-squared=0.603 ; Adjusted R-squared=0.588 ; N=53 A. Regression Model Result Y is net debt issued and deficit is the financing deficit. This deficit is financed with debt and/or equity. If firms follow the pecking order, changes in debt should track changes in the deficit one-for-one. Therefore, the expected coefficient on the deficit is 1. Net Debt Issued From the tables we can conclude that the financing deficit has positive significant effects on net debt issue with t-value of and significance value of This result suggests that high deficit firms would tend to issue more net debt. However, the coefficient on the deficit is and constant value is Net Equity Issued The financing deficit has positive significant effects on net equity issue with t-value of and significance value of This result suggests that high deficit firms would tend to issue more net equity. The coefficient on the deficit is and constant value is Newly Retained Earning The financing deficit has negative but not significant effects on newly retained earning with t- value of and significance value of This result suggests that high deficit firms would not tend to use newly retained earning. The coefficient on the deficit is and constant value is B. Augmented Model Result The augmented model is an alternative means of accounting for a firm s debt capacity. If firms are issuing equity first and debt is the next source of financing, then this relationship should be convex and the coefficient on the squared deficit term would be positive. For the augmented model, our result shows a positive coefficient on the financial deficit and on the squared deficit term. However, for the squared deficit term, the coefficient was not significant. A squared deficit coefficient that is not large in absolute value implies a less reliance on equity finance for values of the financing deficit. Table 6.4. Regression Results of Hypothesis Testing 2 (Issue Debt to Repurchase Equity) Coefficients Model Unstandar dised Co-ef ficients B Std. Error Standardi sed Coefficients Beta t Sig. Collinearity Statistics Tolera nce VIF 113

114 Issue Debt (Constant) FD F=8.354 (0.008) ; R-squared=0.258 ; N=26 Repo (Constant) Equity FD Independent Variable: FD F=0.000 (0.993) ; R-squared=3.18E-6 ; N=26 Issue Debt From the tables we can conclude that the financing deficit has positive significant effects on the net debt issue with t-value of and significance value of This result suggests that high deficit firms would tend to issue more net debt. However, the coefficient on the deficit is and constant value is Repurchase Equity The financing deficit has negative but not significant effects on repurchase equity with t- value of and significance value of This result suggests that high deficit firms would not tend to repurchase equity. The coefficient on the deficit is and constant value is From table , we concluded about firms preferring external or internal financing and prefer debt or equity. Prefer External or Internal Financing? The coefficient of financing deficit on newly retained earning of the firms in the sample is insignificantly negative. The coefficient of financing deficit on net debt and on net equity issue is significantly positive. The coefficient of financing deficit on repurchase equity is insignificantly negative. Therefore, we can conclude that our firms of sample prefer external to internal financing. In addition, the firms would not repurchase equity to finance the deficit. Prefer Debt or Equity? The results of the firms that adopted the pecking order were consistent. The coefficient on the deficit is significantly positive but the coefficient on the deficit-squared is insignificantly positive. It indicates that firms issue debt at the first place, and debt is also the residual source of financing once they have reached their debt capacities. Our evidence seems to suggest firms to rely more heavily on debt financing rather than equity financing and it follows the pecking order theory. The pecking order theory states that changes in debt have played an important role in assessing the pecking order theory. This is because the financing deficit is supposed to drive debt according to this theory. Shyam-Sunder and Myers (1999) examined how debt responded to shortterm variation in investment and earnings. The theory predicts that when investments exceed earnings, debt grows, and when earnings exceed investments, debt falls. Tests of the pecking order 114

115 theory define financing deficit as investments plus change in working capital plus dividends less internal cash flow. The theory predicts that in a regression of net debt issues on the financing deficit, the estimated slope coefficient should be one. The slope coefficient indicates the extent to which new debt issues are explained by financing deficits. Meanwhile, according to Myers (1984) a firm is said to follow a pecking order if it prefers internal to external financing and debt to equity if external financing is used. In the Frank and Goyal (2008) study, the definition of prefer internal financing can be interpreted in two different views. The meaning could be that the firm uses all existing sources of internal finance before issuing any debt or equity or other things equal, that the firm mostly uses internal financing before using external financing. Meanwhile, they imply the strict interpretation of preference of debt over equity which suggested that after the IPO, equity should never be issued unless debt had for some reason become insufficient. This leads to the view of a debt capacity which serves to limit the amount of debt and to allow for the use of equity within the pecking order. Pecking order models can be derived based on adverse selection considerations, agency considerations, or other factors. There seem to be a couple of common features that inspire pecking order theories. The first element is the linearity of the firm s objective function, which means that costs tend to drive the results to corner solutions. The second common element of pecking order models is the relative simplicity of the model (Frank and Goyal, 2008). If we compared the previous research to our result, there were some research findings that were not consistent with our results, for instance, previous research finding from Indonesia, (Ari Christianti, 2008), concluded that: (1) The results of this study did not fully support the pecking order theory in explaining the behaviour of firm financing in the IDX especially the manufacturing sector. This could be explained from the results of the estimation that showed a negative and significant coefficient of pecking order. (2) It might be explained from the results of this study that the Indonesian capital market conditions were different from capital markets in developed countries studied by Shyam-Sunder and Myers (1999), Frank and Goyal (2003) and Jong, Verbeek, and Verwijmeren (2005). In addition, the impact of the economic crisis in 1997 still affected the economic condition of Indonesia until Leary and Roberts (2005) empirically examined the pecking order theory of capital structure using a new empirical model that was motivated by the pecking order's decision rule and implied financing hierarchy. They found that 62% (29%) of the firms in the sample were following the pecking order in their decision between internal and external (debt and equity) financing and that most of the equity issuing violations were not due to debt capacity concerns, as suggested by the modified version of the pecking order. They showed empirically that the pecking order did not seem to be an implication of information asymmetry. The Cotei and Farhat (2008) study concluded that for the pecking order model, the test results rejected the symmetric behaviour assumption at the industry level as well as across all industries. Under the pecking order model, firms in financing deficit used debt to finance their new investment whereas firms in financing surplus ended up retiring debt rather than repurchasing equity. The results showed that firms had the tendency to reduce debt by a significantly higher proportion when they had financing surplus compared to the proportion of debt issued when they had financing deficit. However, there were some research findings which were consistent to our results, for example Sogorb-Mira and López-Gracia (2003) who explored pecking order theory and trade-off 115

116 theory that explained financial policy in Spanish small and medium enterprises (SMEs). The results suggested that both theoretical approaches contributed to explain capital structure in SMEs. Joher, Ahmed, and Hisham (2009) drew on studies from finance and accounting literature to revisit pecking order and static trade-off-hypothesis in the context of the Malaysia capital market. The evidence from the pecking order model suggested that the internal fund deficiency was the most important determinant that possibly explained the issuance of new debt. Hence, pecking order hypothesis is well explained in the Malaysian capital market despite the lower predicting power. Bharath, Pasquariello, Wu (2008) tested whether information asymmetry was an important determinant of capital structure decisions, as suggested by the pecking order theory. They found that information asymmetry did affect the capital structure decisions of U.S. firms. Medeirosa and Daherb tested two models of the static tradeoff theory and the pecking order theory for the capital structure of Brazilian firms. The sample consists of firms listed in the Sao Paulo (Brazil) stock exchange. The result showed that the pecking order theory established that the financial deficit was covered by debt, permitting the issue of new shares in exceptional cases only. Shyam-Sunder and Myers (1994, 1999) tested the traditional capital structure models against the alternative of a pecking order model of corporate financing. The basic pecking order model predicts external debt financing driven by the internal financial deficit. Their main conclusion regarding pot is that the pecking order is an effective first-order descriptor of corporate financing behaviour. Shyam-Sunder and Myers (1999) summarised that the pecking order was an excellent first-order descriptor of corporate financing behaviour, at least for the sample of mature corporations. Their results suggested that firms planned to finance anticipated deficits with debt. The plausible explanation is that the features of the Indonesian economy, with very high real interest rates and reduced long-term credit supply, makes Indonesian firms to avoid long term debt when internally generated resources are available. These resources are usually used to repay debt, which is exactly what the pecking order theory foresees. It should be mentioned that the Indonesian economy and market conditions differ from those under which the tested theories were developed and consequently there are some aspects that need to be pointed out. First, the Indonesian capital market has a secondary role in the capitalisation of Indonesian firms, both in terms of stock or debt issues. Second, Indonesian interest rates, both short and long-term, are very high in real terms. This, together with credit restrictions and the incentive given to banks to invest in government bonds, there is a short supply of private credits. Long-term lending is virtually supplied by the BNDES (the state-owned development bank) only with subsidized interest rates, which is a situation extremely favourable to the pecking order theory Analysis of the Indonesian Condition From our results, we imply that manufacturing firms of the LQ45 Index prefer external to internal financing and debt to equity if external financing is used. It follows the pecking order theory. How do we get our results? Our firm of sample prefers external to internal financing. The plausible explanation is that: 1. Out of 26 firms in our sample, 24 firms are old ones. Older and more mature firms are more closely followed by analysts and are better known to investors and, hence, should suffer less from problems of information asymmetry. The theory s prediction that firms with the greatest information asymmetry problems (specifically young and growth firms) 116

117 are precisely those that should be making financing choices according to the pecking order. However, in Indonesia all listed firms, including older-mature-large and young-growthsmall firms have less problems of information asymmetry as the government of Indonesia has issued the regulations in order to make all listed firms announcing all information about firms. 2. Firms in the manufacturing sector of the LQ45 Index firms have a good reputation to mitigate the adverse selection problem between borrowers and lenders. In Indonesia, by listing on the Indonesia Stock Exchange, banks will be more recognised and trusted than companies. It is not excessive considering each moment banks can determine the condition of the company's financials through various disclosure of information announced by the company in the stock exchange. Rate of interest charged may also be lower considering that the credit risk of public companies is relatively smaller. 3. Furthermore, older firms, more stable and highly profitable firms with few growth opportunities and good credit histories are more suited to use external fund, both debt and equity. Firms also have easier access to the company to enter into money markets through the issuance of debt, both short and long term. Generally, the buyer of a letter of debt would certainly prefer if the company issuing letters of debt has become a public company, especially firms from the LQ45 Index. 4. However, some empirical evidence for the pecking order theory is inconsistent from our results. The plausible explanation is that the Indonesian economy and market conditions differ from those under which the previous research was developed. If firms managers of manufacturing sector of the LQ45 issue equity, the most common motivation based on the pecking order could be adverse selection developed by Myers and Majluf (1984) and Myers (1984). The key idea is that the owner-manager of the firm knows the true value of the firm s assets and growth opportunities. Outside investors can only guess these values. If the manager offers to sell equity, then the outside investor must ask why the manager is willing to do so. In many cases the manager of an overvalued firm will be happy to sell equity, while the manager of an undervalued firm will not. In the Indonesian capital market, by issuing equity, many benefits can be obtained by the company including: obtaining large amounts of funds with costs of fund that are relatively smaller than the funds obtained through banks, the various constraints and problems faced by the company to survive and to develop are becoming the problems of stock holders by participating to think of the best solutions so that the company can continue to grow, any increase in operational performance and financial performance would have an impact on stock prices, which will ultimately increase the value of the company Qualitative Analysis of Hypothesis 2 The following tables 6.5, 6.6a, 6.6b, 6.6c, 6.6d, are our research sample that consists of 26 firms and its classification, namely: growth (16 firms) and mature (10 firms), small (7 firms) and large (19 firms), young (2 firms, INAF and KAEF) and old firms (24 firms). 117

118 Table 6.5. Research Sample No. Firm No. Firm 1 ASII 14 INKP 2 AUTO 15 INAF 3 ADMG 16 INTP 4 BRPT 17 KLBF 5 BUDI 18 KOMI 6 CPIN 19 KAEF 7 DNKS 20 RMBA 8 FASW 21 SMCB 9 GGRM 22 SMGR 10 GJTL 23 TKIM 11 HMSP 24 TSPC 12 INDF 25 UNVR 13 INDR 26 SULI Table 6.6a. Firm Classification over Firm Life Cycle (Growth Firms) No. Firm Life Cycle 1 ADMG Growth 2 BRPT Growth 3 BUDI Growth 4 CPIN Growth 5 DNKS Growth 6 FASW Growth 7 GJTL Growth 8 INDR Growth 9 INKP Growth 10 INAF Growth 11 INTP Growth 12 KOMI Growth 13 SMCB Growth 14 TKIM Growth 15 TSPC Growth 16 SULI Growth Table 6.6b. Firm Classification over Firm Life Cycle (Mature Firms) No. Firm Life Cycle 1 ASII Mature 118

119 2 AUTO Mature 3 GGRM Mature 4 HMSP Mature 5 INDF Mature 6 KAEF Mature 7 KLBF Mature 8 RMBA Mature 9 SMGR Mature 10 UNVR Mature Table 6.6c. Firm Classification over Firm Life Cycle (Small Firms) No. Firm Size 1 BUDI Small 2 DNKS Small 3 INAF Small 4 KOMI Small 5 KAEF Small 6 RMBA Small 7 TSPC Small Table 6.6d. Firm Classification over Firm Life Cycle (Large Firms) No. Firm Size 1 ASII Large 2 ADMG Large 3 BRPT Large 4 CPIN Large 5 FASW Large 6 GGRM Large 7 GJTL Large 8 HMSP Large 9 INDF Large 10 INDR Large 11 INKP Large 12 INTP Large 13 KLBF Large 14 SMCB Large 15 SMGR Large 16 TKIM Large 119

120 % 17 UNVR Large 18 SULI Large 19 AUTO Large Financing Deficit Figure 6.1 implies the financing deficit of each firm, and its dependent variables which illustrated by the following figures. Figure 6.2 shows net debt issue, figure 6.3 explains net equity issue, and figure 6.4 describes newly retained earnings of each firm. Figure 6.1. Financing Deficit of Each Firm 1.4 Financing Deficit of Each Firm firm Note: 1=ASII, 2=AUTO, 3=ADMG, 4=BRPT, 5=BUDI, 6=CPIN, 7=DNKS, 8=FASW, 9=GGRM, 10=GJTL, 11=HMSP, 12=INDF, 13=INDR, 14=INKP, 15=INAF, 16=INTP, 17=KLBF, 18=KOMI, 19=KAEF, 20=RMBA, 21=SMCB, 22=SMGR, 23=TKIM, 24=TSPC, 25=UNVR, 26=SULI The firm that has the highest financing deficit is RMBA (mature-small-old firm), and followed by SMCB (growth-large-old firm), FASW (growth-large-old firm), SULI (growth-largeold firm), INKP (growth-large-old firm), and TKIM (growth-large-old firm). The firm that has the lowest financing deficit is BRPT (growth-large-old firm), and followed by UNVR (mature-largeold firm), TSPC (growth-small-old firm), GGRM (mature-large-old firm), KLBF (mature-largeold firm), and DNKS (growth-small-old firm). 120

121 % % Figure 6.2. Net Debt Issue 0.3 Net Debt Issue firm Note: 1=ASII, 2=AUTO, 3=ADMG, 4=BRPT, 5=BUDI, 6=CPIN, 7=DNKS, 8=FASW, 9=GGRM, 10=GJTL, 11=HMSP, 12=INDF, 13=INDR, 14=INKP, 15=INAF, 16=INTP, 17=KLBF, 18=KOMI, 19=KAEF, 20=RMBA, 21=SMCB, 22=SMGR, 23=TKIM, 24=TSPC, 25=UNVR, 26=SULI The firm that has the highest net debt issue is RMBA, followed by FASW, BUDI, CPIN, HMSP, and INDF. The firm that has the lowest net debt issue is ADMG, followed by SULI, BRPT, KAEF, INTP, and GJTL. Figure 6.3 Net Equity Issue 0.3 Net Equity Issue firm Note: 1=ASII, 2=AUTO, 3=ADMG, 4=BRPT, 5=BUDI, 6=CPIN, 7=DNKS, 8=FASW, 9=GGRM, 10=GJTL, 11=HMSP, 12=INDF, 13=INDR, 14=INKP, 15=INAF, 16=INTP, 17=KLBF, 18=KOMI, 19=KAEF, 20=RMBA, 21=SMCB, 22=SMGR, 23=TKIM, 24=TSPC, 25=UNVR, 26=SULI 121

122 % The firm that has the highest net equity issue is INAF, followed by INAF, BUDI, KOMI, RMBA, and SMCB. The firm that has the lowest net equity issue is KAEF, followed by GGRM, INDF, KLBF, ASII, and HMSP. Figure 6.4. Newly Retained Earning 0.2 Newly Retained Earning firm Note: 1=ASII, 2=AUTO, 3=ADMG, 4=BRPT, 5=BUDI, 6=CPIN, 7=DNKS, 8=FASW, 9=GGRM, 10=GJTL, 11=HMSP, 12=INDF, 13=INDR, 14=INKP, 15=INAF, 16=INTP, 17=KLBF, 18=KOMI, 19=KAEF, 20=RMBA, 21=SMCB, 22=SMGR, 23=TKIM, 24=TSPC, 25=UNVR, 26=SULI The firm that has the highest NRE is KAEF, followed by GGRM, KOMI, UNVR, TSPC, ADMG, and HMSP. The firm that has the lowest NRE is SMCB, followed by FASW, BRPT, SULI, INTP, INKP, and TKIM. Capital Structure Figure 6.5 implies firms capital structure which consists of newly retained earning, net equity issue, and net debt issue overall of 26 firms. Meanwhile, figure 6.6 shows aggregates of financial deficit, these are long-term leverage, fixed asset, dividend, change in working capital, and net income, where all aggregates are divided by total asset. Figure 6.5. Firms Capital Structure Capital Structure 0.2 % Note:1=newly retained earning, 2=net equity issue, 3=net debt issue 122

123 % The capital structure which has the highest composition to overcome financing deficit is the net debt, followed by the net equity. It is supported also by the results of regression tests which concluded that the net debt issues, instead of the net equity issues, are more influenced by the financial deficit of the company. Figure 6.6. Aggregate of Financial Deficit Agregate of Financial Deficit =LTL/TA 2=FA/TA 3=DIV/TA 4=change in WC/TA 5=NI/TA The highest aggregate of financial deficit is fixed asset to total asset while the lowest is long-term liability to total asset. The firms which have issued more net debt than net equity are ASII, AUTO, BUDI, CPIN, DNKS, FASW, GGRM, HMSP, INDF, INDR, INKP, KLBF, RMBA, SMGR, TKIM, TSPC, and UNVR. The firms consist of growth firms (8 firms including BUDI, CPIN, DNKS, FASW, INDR, INKP, TKIM, and TSPC), and mature firms (9 firms including ASII, AUTO, GGRM, HMSP, INDF, KLBF, RMBA, SMGR, and UNVR). Hence, the 17 mentioned firms follow pecking order theory. The firms which have issued more net equity than the net debt are ADMG, BRPT, GJTL, INAF, INTP, KOMI, KAEF, SMCB, and SULI. All of these firms are growth firms except KAEF. Newly Retained Earning, Net Debt Issue, Net Equity Issue, and Financing Deficit Table 6.7 describes a firm s capital structure. Within the research period of , firms that had a negative average of newly retained earning were BRPT, FASW, INKP, INTP, SMCB, and SULI. All of these 6 firms were growth firms, while five out of six firms were large firms except SULI. However, two out of six firms, INKP and SMCB have ever had the negative net equity while they had positive net debt. Within the research period of 14 years, the firm that had a negative average of net equity issue was KAEF as a mature-small-young firm. Meanwhile, firms that had a negative average of net debt issue were ADMG, BRPT, INTP, KAEF, and SULI. Four out of five firms were growth firms except for KAEF, and three out of five firms were large firms except for KAEF and SULI. Negative average of net debt issue indicated that firms paid their debt. Table 6.7. The Firm s Capital Structure Firms FD NDEBT NEQUITY NRE ASII AUTO

124 ADMG BRPT BUDI CPIN DNKS FASW GGRM GJTL HMSP INDF INDR INKP INAF INTP KLBF KOMI KAEF RMBA SMCB SMGR TKIM TSPC UNVR SULI Interestingly, KAEF had the negative average of net debt and net equity issue, it indicated that the firm paid the debt and repurchased the equity within the research period. However, within the research period of 14 years, all firms have experienced the financing deficit which was indicated by the positive sign of financing deficit. BRPT, INTP, and SULI, had the negative sign of net debt issue and newly retained earning; it implied that even though they had negative newly retained earning, they decided to pay their debt. All of the firms were growth firms which did not pay dividend regularly in six years. Issue Debt to Repurchase Equity Table 6.8 shows the value of newly retained earning, net debt issue, net equity issue, and financing deficit. ASII had a negative value of net equity and a positive value of net debt in the years 2000, 2005, and ADMG had a negative net equity and a positive net debt in CPIN had a negative net equity and a positive net debt in DNKS had a negative value of net equity and a positive net debt in the year 2000 and GGRM had a negative value of net equity and positive net debt in 2000, 2001, and GJTL had a negative value of net equity and positive net debt in the year 1998, 2000, and HMSP had a negative net equity and positive net debt in

125 INDF had a negative net equity and a positive net debt in INKP had a negative net equity and a positive net debt in the years 1999 and INAF had a negative net equity and a positive net debt in KLBF had a negative value of net equity and a positive net debt in the years 1997, 2001, and SMCB had a negative net equity and a positive net debt in SMGR had a negative net equity and a positive net debt in UNVR had a negative value of net equity and positive net debt in Table 6.8. The Value of Newly Retained Earning, Net Debt Issue, Net Equity Issue, and Financing Deficit Firms Year Newly Retained Earning ASII (large-mature firm) ADMG (large-growth firm) CPIN (large-growth firm) DNKS (small-growth firm) GGRM (large-mature firm) GJTL (large-growth firm) HMSP (large-mature firm) INDF (large-mature firm) INKP (large-growth firm) Repurchase Equity 125 Issue Debt Financing Deficit E E

126 INAF (small-growth firm) KLBF (large-mature firm) SMCB (large-growth firm) SMGR (large-mature firm) UNVR (large-mature firm) E E Table 6.8 shows the value of newly retained earning, net debt issue, net equity issue, and financing deficit. It shows that firms that have negative net equity issue are ASII, ADMG, CPIN, DNKS, GGRM, GJTL, HMSP, INDF, INKP, INAF, KLBF, SMCB, SMGR, and UNVR. It implies that the firms have repurchased their equity. However, based on regression result, coefficient of correlation obtained from variable net debt issue and repurchase equity is negative but not significant. It explains that firm s has not issued debt to repurchase their equity. Coefficient of correlation obtained from variable net debt and financing deficit is positive significant. It explains that firm s issued debt to solve their financing deficit. Half of the firms which repurchase equity are mature firms and the rest are growth firms. However, 12 out of 14 firms repurchase equity of large firms while the rest repurchase equity of small firms. It means that repurchase equity is mostly done by large firms which have large amount of total asset. ASII repurchased its equity in 2000, 2005, and 2007 with the percentages of 9.45%, 0.067%, and 0.174%. ADMG repurchased its equity in 2001 with the amount of 0.147%. CPIN repurchased its equity in 1998 with the amount of 2.2%. DNKS repurchased its equity in with the amount of 0.45% and 0.045%. GGRM repurchased its equity in 2000, 2001, 2003 with the amount of 0.014%, E-03%, and E-03%. GJTL repurchased its equity in 1998, 2000, 2001, with the amount of 0.138%, 0.58%, 0.169%. HMSP repurchased its equity in 2001 with the amount of 1.22%, INDF repurchased its equity in 2002 with the amount of 3.14%, and INKP repurchased its equity in 1999 and 2003 with the amount of 4.58%, 2.18%. INAF repurchased its equity in 2002 with the amount of E-04%, KLBF repurchased its equity in 1997, 2001 and 2007 with the amount of 0.702%, 0.02%, 2.36%. SMCB repurchased its equity in 1999 and 2000 with the amount of 26.4%, 0.49%. SMGR repurchased its equity in 1998 and 2000 with the amount of E-05%, %. UNVR repurchased its equity in 1998 and 2000 with the amount of %. These indicate that in these mentioned years, the firms have more excess funds. 126

127 The positive sign of net debt issue, the negative sign of net equity issue, the positive sign of newly retained earning and financing deficit at the same time, indicated that the 14 firms have issued debt, decreased their equity composition, at the time they had newly retained earning and they were experiencing financing deficit. It indicates that mature firms issue debt, pay dividend, and repurchase their equity, when they have newly retained earning. However, the 3 remaining mature firms AUTO, KAEF, and RMBA have not repurchased equity and it meant that the firms preferred to pay dividend to repurchase equity when they had excess funds. Surplus Table 6.9 implies the firm s surplus. Based on annual average data of financing deficit, firms which experienced a surplus during the period of study were ASII, ADMG, BRPT, GJTL, INAF, KLBF, KAEF, RMBA, TSPC, and UNVR. ASII had a surplus of 7.2% in ADMG had a surplus of 28% in BRPT experienced a surplus of 76% and 26% in GJTL had 65% surplus in INAF had a surplus of 13% and 1.65% in KLBF had surplusses of 3.5%, 15.86%, and 9.06% in 1997, 2002, and KAEF had a surplus of 14.05% in RMBA had a 4.83% surplus in TSPC had a 9.83% and a 55.81% surplus in the years 1996 and UNVR had surplusses in the year 2000, 2003, 2004, and 2006 of 2.38%, 10.7%, 1.71%, and 17.37%. Table 6.9. Firm s Surplus Firm Year % Surplus ASII Surplus ADMG Surplus BRPT Surplus Surplus GJTL Surplus INAF Surplus Surplus KLBF Surplus Surplus Surplus KAEF Surplus RMBA Surplus TSPC Surplus Surplus UNVR Surplus Surplus Surplus Surplus ASII, KLBF, KAEF, RMBA, and UNVR are mature firms, while the rest are growth firms. Although all five firms are mature firms that indicate they are the dividend payer, those firms still have a surplus because their cashflows exceed the dividend, capital expenditure, current 127

128 assets, and the LTD payment. ASII, ADMG, BRPT, GJTL, KLBF, and UNVR are large firms, while the rest are small firms. UNVR is the most frequently experienced the surplus (4 years), KLBF got 3 years of surplus, BRPT, INAF, and TSPC got 2 years of surplus, ASII, ADMG, GJTL, KAEF, and RMBA got 1 year of surplus. Correlations Analysis Table 6.10 implies that profitability and newly retained earning have positive significant correlations, which means that the firm which has higher profitability can issue more newly retained earning. Tangibility and newly retained earning have negative significant correlations. It means that the firms which issue more newly retained earning have lower tangibility. Size and newly retained earning have negative but not significant correlation, growth and newly retained earning have negative but not significant correlation. It means that the firm which issue more newly retained earning has smaller size, and lower growth, but not significant. Risk and newly retained earning have negative significant correlation, it means that the firm which issue more newly retained earning has lower risk, and significance. Table 6.10a. Correlations between Variables NRE NEQUITY NDEBT FD NRE Pearson Correlation ** ** Sig. (2-tailed) NEQUITY Pearson Correlation **.225 ** Sig. (2-tailed) NDEBT Pearson Correlation ** ** ** Sig. (2-tailed) FD Pearson Correlation **.225 **.347 ** 1 Sig. (2-tailed) Table 6.10b. Correlations between Variables PRFT TANG SIZE RISK GROWTH NRE Pearson Correlation.654 ** ** ** Sig. (2-tailed) NEQUIT Pearson Correlation * Y Sig. (2-tailed) NDEBT Pearson Correlation Sig. (2-tailed) FD Pearson Correlation **.551 **.150 * Sig. (2-tailed) Growth and net equity issue have negative but not significant correlation, profitability and net equity issue have negative but not significant correlation; it means that the firm which has higher profitability and higher growth issues less net equity, but not significantly. Tangibility and 128

129 net equity issue have positive but not significant correlation, risk and net equity issue have positive but not significant correlation, it means that the firm which has higher tangibility and higher risk issues more net equity, but not significantly. Size and net equity issue have negative significant correlation, it means that the firm which has larger size and issue less net equity, and significantly. Profitability and net debt issue have negative but not significant correlation, tangibility and net debt issue have negative but not significant correlation, size and net debt issue have negative but not significant correlation, growth and net debt issue have negative but not significant correlation; it means that the firm which has larger size, higher profitability, tangibility, and growth, issues less net equity, but not significantly. Risk and net debt issue have positive but not significant correlation. It means that the firm which has higher risk, issues more net debt, but not significantly. Profitability and financing deficit have negative significant correlation; it means that the firm which has higher financing deficit has lower profitability, and the correlation is significant. Growth and financing deficit have negative but not significant correlation; it means that the firm which has higher financing deficit has lower growth, but it is not significant. Tangibility and financing deficit have positive significant correlation, Size and financing deficit have positive significant correlation, it means that the firm which has higher financing deficit, is a larger firm, and has higher asset tangibility, and the correlation is significant. Risk and financing deficit have positive but not significant correlation, it means that the firm which has higher financing deficit, is high risk firm, but not significant Research Question 3, Hypothesis, Hypothesis Testing, and Result Analysis As applied in hypothesis 1, we also use quantitative strategy in testing hypothesis 3. The following sub-sections are explaining research questions three, hypotheses three, hypotheses testing three, and results analysis Research Question Three Based on the asymmetric information and signalling theory, our major and minor research questions are as follow: Does debt policy matter? (a) If firms issue new debt, what will happen to the firm s stock price? (b) If firms issue new equity, what will happen to the firm s stock price? (c) If firms issue debt to repurchase equity, what will happen to the firm s stock price? Hypothesis 3 By formulating research question three, therefore, our major and minor hypotheses three are as follow: Debt does policy matter. (a) If firms issue new debt, then the firms s stock price will be higher. (b) If firms issue new equity, then the firms s stock price will be lower. (c) If firms issue debt to repurchase equity, then the firms s stock price will be higher. 129

130 Testing the Hypothesis 3 As described in chapter 5, multiple regression analysis is selected to test hypothesis 3. For testing hypothesis 3, the independent variables are the net debt issue, the net equity issue, and the debt issued to repurchase equity, whereas the dependent variable is stock price. The objective of regression analysis is to examine to what extent the influence of those independent variables Analysis of Results The following sub-chapters are consisting of analysis of result and consistency of result with the theory and previous research, and also how its condition in Indonesia capital market Analysis of Result and Its Consistency with the Theory and Previous Research Table shows the regression results of hypothesis testing 3a, 3b, and 3c, which tested net debt issue, net equity issue, and net debt issue to repurchase equity, on monthly and yearly stock price. A. Regression Results of Hypothesis 3a Table 6.11 explains the influence of net debt issue on stock price from January to December and the impact of net debt issue on the yearly stock price. Table Regression Results of Hypothesis Testing 3a Coefficients a Model Jan Feb Mar Apr May Jun Jul Aug Sep Oct Unstanda rdised Coefficients Standardi sed Coefficients 130 t Sig. Collinearity Statistics B Beta Tolera nce VIF (Constant) NDEBT (Constant) NDEBT (Constant) NDEBT (Constant) NDEBT (Constant) NDEBT (Constant) NDEBT (Constant) NDEBT (Constant) NDEBT (Constant) NDEBT (Constant) NDEBT (Constant)

131 Nov NDEBT (Constant) Dec NDEBT yearly (Constant) NDEBT Dependent Variable: P_yearly F=0.146 (0.702) ; R-squared=0.001 ; N=196 The t-values of net debt on January to June were 1.789; 1.727; 1.749; 1.673; 1.722; and But these t-values did not have the significance value of 0.077; 0.088; 0.084; 0.098; 0.089; and consecutively. Actually, stock price from January to June got almost the positive significant impact, but it needed more data and a longer period of sampling to make the result significant. The t-values of net debt on stock price from July to December were 1.652; 1.639; 1.590; 1.604; 1.589; and Those, t-value did not have the significance value of 0.102; 0.105; 0.115; 0.112; 0.115; and consecutively from January to December. It indicated that net debt got no significant impact on the stock price of January to December. The t-value of net debt on yearly stock price was and got positive but not significance value of This indicated that net debt got no significant impact on the yearly stock price. Here is the explanation of our result. When we compared the results to the theory of predictions, we first analysed the theory of predictions for debt issues and equity issues. When a firm issued, repurchased or exchanged one security for another, it changed its capital structure. What were the valuation effects of these changes? There were several theories that explained the relationship between capital structure and stock price. Along with the increased level of leverage accompanied by higher risk of bankruptcy, the increased level of debt indicates the confidence level of the management in the future. Hence, it carries greater conviction than a mere announcement of undervaluation of the firm, by the management. On the other hand, an issue of equity is a signal that the firm is overvalued. The market concludes that the management has decided to offer equity because it is valued higher than it has been valued intrinsically by the market. The markets normally react favourably to moderate increases in leverage and negatively to fresh issue of equity. Under the trade-off theory, the market reaction to both equity and debt securities will be the following: (1) Debt issues. The market response to a leverage change confounds information: necessitating financing and the effect of the financing on security valuations. The information contained in security issuance decisions could be either good news or bad news. It would be good news if the firm is issuing securities to take advantage of a promising new opportunity that was not previously anticipated. It might be bad news if the firm is issuing securities because the firm actually needs more resources than anticipated to conduct operations. (2) Equity issues. Jung et al. (1996) suggested an agency perspective and argued that equity issues by firms with poor growth prospects reflected agency problems between managers and shareholders. If this is the case, then stock prices would react negatively to news of equity issues. The pecking order theory is usually interpreted as predicting that securities with more adverse selection (equity) will result in more negative market reaction. Securities with less adverse 131

132 selection (debt) will result in less negative or no market reaction. This of course, still rest on some assumptions about market anticipations. Conclusion: Our result is positive. Therefore, our result is consistent with signalling through capital structure, as the increased level of leverage is accompanied by higher risk of bankruptcy, the increased level of debt indicates the confidence of the management in the future. Hence it carries greater conviction than a mere announcement of undervaluation of the firm by the management. Our result is also consistent with the pecking order theory, as securities with less adverse selection (debt) will result in less negative or no market reaction. Finally, our result is in line with trade off theory. If the firm issued securities to take advantage of a promising new opportunity, so it would be good news to the market. If compared to previous empirical evidence, our result is consistent with the following findings, for example, announcements of ordinary debt issues generate zero market reaction on average (Eckbo (1986) and Antweiler and Frank (2006)). The zero market reaction to corporate debt issues is robust to various attempts to control for partial anticipation. Meanwhile, exchange of common for debt/preferred stock generates positive stock price reactions while exchange of debt/preferred for common stock generates negative reactions (Masulis, 1980a). Eckbo and Masulis (1995) concluded that announcements of security issues typically generated a non-positive stock price reaction. Ross (1977) showed that good corporate performance could give a signal with a high portion of debt in their capital structure. Ross (1977) assumed firms that were less well performancing would not use debt in large portion as it would be followed by the high chance of bankruptcy. By using these assumptions in which the company will use the good performance of higher debt, while firms that are less good performance will use more of equity. Ross (1977) assumed that investors would be able to distinguish the company's performance by looking at the company's capital structure and they will give a higher value on the company with larger debt portion. It indicates that the result do not support the stated of signalling theory. The result indicates that the greater the leverage, the greater the possibility of financial distress leading to bankruptcy. When the company went bankrupt, shareholders would lose money they invest in the company (Peirson et al, 2002). However, our result is inconsistent with the following empirical evidence. In Indonesia, the regression coefficient between leverage and stock price is significantly negative. The use of high leverage will be responded by the market with a fall in stock prices. These results are consistent with the findings of a negative relationship between leverage and stock price as proposed by Frank and Goyal (2003). Relationship between the two variables will be positive at the time the company has many tangible assets that will secure leverage of companies. Announcements of convertible debt issues resulted in mildly negative stock price reactions (such as Dann and Mikkelson, 1984; Mikkelson and Partch, 1986). The valuation effects are the most negative for common stock issues, slightly less negative for convertible debt issues and least negative (zero) for straight debt issues. The effects are more negative the larger the issue. The reason of why firms issue debt could be the intention to take advantage, eventhough there would be the disadvantages of debt. Indonesia companies face the challenge of determining whether to issue debt or equity for financing needs. 132

133 B. Regression Result of Hypothesis 3b The following table 6.12 explains the influence of net equity issue on stock price from January to December and the impact of net equity issue on the yearly stock price based on regression results. Table Regression Result of Hypothesis Testing 3b Coefficients Model Unstandar dised Coef ficients Standar dised Coefficients t Sig. Collinearity Statistics B Beta Tolera VIF nce (Constant) Jan NEQUITY (Constant) Feb NEQUITY (Constant) Mar NEQUITY (Constant) Apr NEQUITY (Constant) May NEQUITY (Constant) Jun NEQUITY (Constant) Jul NEQUITY (Constant) Aug NEQUITY (Constant) Sep NEQUITY (Constant) Oct NEQUITY (Constant) Nov NEQUITY (Constant) Dec NEQUITY (Constant) Yearly NEQUITY Dependent Variable: P_yearly, F=0.872 (0.352) ; R-squared=0.004 ; N=196 The t-value of net equity on stock price of January to December were ; ; ; ; ; ; ; ; ; ; ; and It did not have the significance-value of 0.533; 0.539; 0.536; 0.529; 0.535; 0.530; 0.454; 0.459; 0.433; 0.465; 0.475; and consecutively from January to December. 133

134 The t-value of net equity on yearly stock price was and got negative but not significance value of This indicated that net equity had no significant impact on the yearly stock price. This result suggests that firms that issue more net equity would tend to have decreasing stock price. Thus, we fail to reject the hypothesis that if firms issue new equity, then the firm s stock price will be lower. Here is the explanation of our result. When we compared the results to the theory of predictions, our results were consistent with the theory of signalling through capital structure, pecking order theory, and Jung et al. (1996). Jung et al. (1996) suggested an agency perspective and argued that equity issues by firms with poor growth prospects reflected agency problems between managers and shareholders. If this is the case, then stock prices would react negatively to news of equity issues. Our results were consistent with the following empirical evidence, for instance, announcements of equity issues resulted in significant negative stock price reactions (Asquith and Mullins Jr., 1986; Masulis and Korwar, 1986; and Antweiler and Frank, 2006). The negative market reaction to equity issues and zero market reaction to debt issues are consistent with adverse selection arguments. Indeed, there is other interpretation. Jung et al. (1996) showed that firms without valuable investment opportunities experienced a more negative stock price reaction to equity issues than did firms with better investment opportunities. Thus, agency cost arguments could also explain the existing evidence on security issues. Further support for the agency view came from the finding that firms without valuable investment opportunities issuing equity invested more than similar firms issuing debt and that firms with low managerial ownership had worse stock price reaction to new equity issue announcements than did firms with high managerial ownership. Meanwhile, our results were inconsistent with the following empirical evidence. The impact of equity issues appears to differ between countries. Several studies found positive market reaction to equity issues around the world (Eckbo et al., 2007). To understand this evidence, Eckbo and Masulis (1992) and more recently Eckbo and Norli (2004) examined stock price reactions to equity issues conditional on a firm s choice of flotation method. Firms can issue equity using uninsured rights, standby rights, firm commitment underwriting and private placements. The stock price reactions to equity issues depend on the floatation method. For U.S. firms Eckbo and Masulis (1992) it was found that the average announcement-period abnormal returns were insignificant for uninsured rights offerings and they were significantly negative for firm-commitment underwritten offerings. Eckbo and Norli (2004) studied equity issuances on the Oslo Stock Exchange. They found that uninsured rights offerings and private placements resulted in positive stock price reactions while standby rights offerings generated negative market reactions. These papers interpreted the effect of the flotation method as reflecting different degrees of adverse selection problems. C. Regression Result of Hypothesis 3c Table 6.13 shows the influence of net debt issue and repurchase equity on stock price from January to December and the impact of net debt issue and repurchase equity on the yearly stock price. Table Regression Result of Hypothesis Testing 3c (Firms which Repurchased Stock) Model Unstandar dised Coefficients Standar Dised Coefficients t Sig. Collinearity Statistics 134

135 B Beta Tolera VIF nce Jan (Constant) NDEBT NEQUITY Feb (Constant) NDEBT NEQUITY Mar (Constant) NDEBT NEQUITY Apr (Constant) NDEBT NEQUITY May (Constant) NDEBT NEQUITY Jun (Constant) NDEBT NEQUITY Jul (Constant) NDEBT NEQUITY Aug (Constant) NDEBT NEQUITY Sep (Constant) NDEBT NEQUITY Oct (Constant) NDEBT NEQUITY Nov (Constant) NDEBT NEQUITY Dec (Constant) NDEBT NEQUITY Yearly (Constant) NDEBT NEQUITY Dependent Variable: P_yearly, F=1.491 (249) ; R-squared=0.130 ; Adjusted R- squared=0.043 ; N=23 The t-value of repurchasing equity on stock price of January to December was positive but the result was not significant. The t-value of repurchasing equity on yearly stock price was positive but neither was it significant. 135

136 This result suggested that the firms that repurchased equity would tend to have increasing stock price. Thus, we failed to reject the hypothesis that if firms repurchased equity, then the firm s stock price would be higher. Negative sign means that the more the debt is issued, the lower the price goes, whereas a positive sign means the more the firms repurchase equity, the higher the price goes. Based on undervaluation hypothesis: Repurchases and investment policy: repurchasing stock offered flexibility not only for the option taken on distributing the excess of funds but also when to distribute these funds. This flexibility in timing is beneficial because firms can wait to repurchase until the stock price is undervalued. The undervaluation hypothesis is based on the premise that information asymmetry between insiders and shareholders may cause a firm to be misvalued. If insiders believe that the stock is undervalued, the firm may repurchase stock as a signal to the market to invest in its own stock and acquire mispriced shares. According to this hypothesis, the market interpreted the action as an indication that the stock was undervalued (in Amy K. Dittmar (1999). Because of the asymmetric information between managers and shareholders, share repurchase announcements are considered to reveal private information that managers have about the value of the company. The signalling hypothesis has three immediate implications: repurchase announcements should be accompanied by positive price changes; repurchase announcements should be followed (though not necessarily immediately) by positive news about profitability or cash flows; and repurchase announcements should immediately be followed by positive changes in the market s expectation about future profitability (in Gustavo Grullon and Roni Michaely, 2002). When we compared the results to the previous research, many studies showed that repurchases were associated with a positive stock price reaction, for example Vermaelen (1981), Dann (1981), and Comment and Jarell (1991) found that the positive stock price reaction at the announcement of a stock repurchase program should correct the misevaluation. Ikenberry, Lakonishok and Vermaelen (1995) showed that this increase might not be sufficient to correct the price since the repurchasing firms, particularly low market to book firms, have earned a positive abnormal return during the four years subsequent to the announcement. The amount of information available and the accuracy of the valuation of firms by the market can affect firms repurchase decisions. Ikenberry et al. (1995) have studied abnormal returns following share repurchase announcements. They found out that the average instant (two days before through two days after) reaction to the announcement was 3.54 percent. The average long-term (four-year buy-and-hold) abnormal return was 12.1 percent. According to Jensen (1986), firms repurchased stock to distribute the excess of cash flow. Stephens and Weisbach (1998) supported this hypothesis, as they found a positive relation between repurchases and the levels of cash flow. Stephens and Weisbach also showed that repurchase activity was negatively correlated with prior stock returns, indicating that firms repurchased stock when their stock prices were perceived as undervalued. This result agrees with Vermaelen s (1981) findings that firms repurchase stock to signal undervaluation. Thus, firms repurchase stock when they are undervalued and have the excess of cash to distribute. Masulis (1980b), Dann (1981), and Antweiler and Frank, (2006) also found that the announcement effects were positive when common stock was repurchased. Brav et al. (2005.b.) discovered on their survey that only 22.5 percent of executives believed that reducing repurchases had negative consequences. On the other hand, almost 90 percent thought that reducing dividends had negative consequences. 136

137 Overall, our result is in line with the signalling hypothesis that has immediate implications: repurchase announcements should be accompanied by positive price changes. It is also consistent with many empirical evidences Analysis of the Indonesian Condition In Indonesia, why can the stock price go up and down? Stock price movements are determined by supply and demand for these shares. Demand increases, the stock price increases and vice versa. Factors that affect stock price movements include the movements in interest rates, inflation, exchange rate of the Rupiah, performance of the company such as sales and profit increases, for dividends and so on. Non-economic factors including social and political conditions also influenced the firm s stock price. Stock price movements are determined by the issue of equity and debt. Firms in the manufacturing sector of the LQ45 Index take the advantages of debt compared to equity. Issuance of debt has a tax benefit because of the debt tax shield. A company with a higher tax rate thus has a higher tax benefit from debt issuance. Some assert that debt adds discipline to management because interest expenses cause lower cash flows, which makes management more likely to be efficient. Hence, debt issue has positive effect on stock price. Meanwhile, firms in the manufacturing sector of the LQ45 Index face the problems because of increasing using leverage, even though the firms have high asset tangibility to secure their debt. The firms have a risk of bankruptcy. Additionally, unlike equity, debt must at some point be repaid. High interest costs during difficult financial periods can increase the risk of insolvency, and companies that are too highly leveraged (that have large amounts of debt as compared to equity) often find it difficult to grow because of the high cost of servicing the debt. Therefore, our result shows that the positive influence of debt issue on stock price is not significant Research Question 4, Hypothesis, Hypothesis Testing, and Result Analysis In this study, the research question, hypothesis, hypothesis testing, and result analysis four are explained in the follow sub-sections: Research Question 4 Our research question 4 is, in the context of firm s life cycle, can we expect that growth [and small] firms follow the pecking order theory more closely than mature [and large] firms? Hypothesis 4 As our hypothesis 4 state that, in the context of a firm s life cycle, we expect that growth [and small] firms follow the pecking order theory more closely than mature [and large] firms, hence, we test this hypothesis applying multiple regression and augmented analysis as in hypothesis 2, but in the context of firm s life cycle Testing Hypothesis 4 As described in chapter 5, multiple regression analysis and augmented analysis were selected to test hypothesis 4. For testing hypothesis 4, the independent variable was financing deficit and net debt issue and net equity issue, were the dependent variables. The objective of regression analysis is to examine which firm is more following the pecking order theory, growth firms or mature firms. If firms followed the pecking order theory, the 137

138 deficit is financed with internal financing, for external financing, the financing deficit is financed with debt first then equity. The firms adopted the pecking order have the changes in debt with track changes in the deficit one-for-one. Hence, the expected coefficient on the deficit is 1. The objective of augmented analysis is to examine how growth and mature firms finance the deficit, with debt first or equity first. If firms followed the pecking order, changes in debt should track changes in the deficit one-for-one (Shyam-Sunder and Myers, 1999). If firms financed their deficit with debt first and issued equity only when they reached their debt capacities, then net debt issued was a concave function of the deficit (Chirinko and Singha, 2000) and the coefficient on the squared deficit term would be negative. If firms issued equity first and debt was the residual source of financing, then this relationship should be convex and the coefficient on the squared deficit term would be positive Sample Description Table 6.14 is divided into the following tables 6.14a, 6.14b, 6.14c, 6.14d, and 6.14e, which are our samples of mature/growth, large/small, and young/old firms. From the tables, we can see that all mature firms are large firms except the KAEF and RMBA, all mature firms are old firms except KAEF, all small firms are growth firms except KAEF and RMBA, all firms are old firms except INAF and KAEF. Table 6.14a. Firm Classifications: Growth Firms Growth Firms ADMG BRPT BUDI CPIN INKP INAF INTP KOMI DNKS FASW GJTL INDR SMCB TKIM TSPC SULI Table 6.14b. Firm Classifications: Mature Firms Mature Firms ASII AUTO GGRM HMSP INDF KAEF KLBF RMBA SMGR UNVR Table 6.14c. Firm Classifications: Small Firms Small Firms BUDI DNKS INAF KOMI KAEF RMBA TSPC Table 6.14d. Firm Classifications: Large Firms Large Firms ASII AUTO ADMG BRPT CPIN FASW GGRM GJTL HMSP INDF INDR INKP INTP SULI KLBF SMCB SMGR TKIM UNVR 138

139 Table 6.14e. Firm Classifications: Old and Young Firms Old Firms ASII AUTO ADMG BRPT CPIN FASW GGRM GJTL BUDI DNKS INDR INKP INTP KLBF KOMI RMBA TKIM TSPC UNVR SULI SMCB SMGR HMSP INDF Young Firms INAF KAEF Bulan, Subramanian, and Tanlu (2007) found that firms that initiated dividends were mature firms. Thus, Bulan and Yan (2007) identified firms in their mature stage by their dividend history. By following Bulan and Yan (2007) to construct the growth and mature sample firms, to deem the 6-year dividends payment periods as the mature stage of a firm s life cycle, we found 10 firms which have one 6-year dividend payment period; while 16 firms have less than one 6-year dividend payment periods. Meanwhile, 8 of our 10 mature firms are large firms, except KAEF, RMBA. KAEF went public on July 4, Its amount of total assets made KAEF was categorised as a small firm (Hufft, JR category). It was established on January 23, 1969 and the firm was a dividend payer. Based on those facts, KAEF is a small young mature firm that is liquid enough to pay dividend to the shareholder. RMBA is a small mature old firm that pays dividend for 6 years consecutively (Bulan and Yan, 2007). We have 7 small firms and 19 large firms based on the Hufft category with total assets of less than $150 million, or equal to IDR 1,081, ,086, million. Our sample of firms which were categorised into young firms, based on Evans (1987) who defined firms of six years old or younger as young firms and firms of seven years or older as old firms, were INAF and KAEF. INAF was established on January 2, 1996 and went public on April 17, INAF is also a small-growth firm. KAEF was established on January 23, 1969 and went public on July 4, INAF is a small-mature firm Analysis of Results The following sub-sections are analysis of results for growth and mature firms and its consistency with the theory and previous research, and also with the Indonesian capital market condition Analysis of Results and Its Consistency to the Theory and Previous Research (Growth and Mature Firms) As shown by table , the regression result for mature and growth firms are as follow: The financing deficit is financed with debt and/or equity. If firms follow the pecking order, changes in debt should track changes in the deficit one-for-one. Therefore, the expected coefficient on the deficit is 1. Table Regression and Augmented Results for Mature Firms Coefficients a Model Unstandardised Coefficients B Std. Error Standar dised Coefficients Beta 139 t Sig. Collinearity Statistics Tolera nce VIF

140 NDebt_ (Cons M tant) FD_M F= (0.000) ; R-squared=0.147 ; N=92 NEquity (Cons _M tant) FD_M F=6.196 (0.015) ; R-squared=0.064 ; N=92 NRE_M (Cons tant) FD_M F=2.921 (0.091) ; R-squared=0.031 ; N=92 NDebt_ (Cons M tant) FD_M FDSQR_ M Independent Variable: FD F= (0.000) ; R-squared=0.245 ; Adjusted R-squared=0.229 ; N=92 Table Regression and Augmented Results for Growth Firms Coefficients Model Unstandardised Coefficients B Std. Error NDebt _G F= (0.000) ; R-squared=0.148 ; N=132 NEquit y_g F=4.219 (0.042) ; R-squared=0.031 ; N=132 NRE_ G F= (0.001) ; R-squared=0.081 ; N=132 NDebt _G Standar Dised Coefficients Beta t Sig. Collinearity Statistics Tolera nce VIF (Constant) FD_G (Constant) FD_G (Constant) FD_G (Constant) FD_G FDSQR_G Independent Variable: FD F= (0.000) ; R-squared=0.285 ; Adjusted R-squared=0.273 ; N=132 A. Growth Firms Our regression model results of financing deficit on net debt issue, net equity issue, and newly retained earning for growth firms are as follow: 140

141 Regression Model Result In the regression model, Y is net debt issued and deficit is the financing deficit. This deficit is financed with debt and/or equity. If firms follow the pecking order, changes in debt should track changes in the deficit one-for-one. Therefore, the expected coefficient on the deficit is 1. Net Debt Issue From the tables we can conclude that the financing deficit has positive significant effects on net debt issue with t-value of (it higher than mature firms) and significance value of This result suggests that high deficit firms would tend to issue more net debt. However, the coefficient on the deficit is and constant value is Net Equity Issue The financing deficit has positive but not significant effects on net equity issue with t- value of (it lower than mature firms) and significance value of This result suggests that high deficit firms would tend to issue more net equity. However, the coefficient on the deficit is and the constant value is Newly Retained Earning The financing deficit has negative significant effects on newly retained earning with t- value of (it more negative than mature firms) and significance value of This result suggests that high deficit firms would not tend to use newly retained earning. However, the coefficient on the deficit is and constant value is Augmented Model Result If firms are issuing equity first and debt is the residual source of financing, then this relationship should be convex and the coefficient on the squared deficit term would be positive. However, our result shows a negative coefficient on the squared deficit term, it implies that firms are limited by their debt capacity constraints and they have to resort to issuing equity. A squared deficit coefficient that is large in absolute value implies a greater reliance on equity finance for larger values of the financing deficit. From these results, we can conclude that our sample of growth firm in the manufacturing sector of the LQ45 Index prefers external to internal financing and debt to equity if external financing is used. This is consistent with the theory s prediction that firms with the greatest information asymmetry problems (specifically young, growth firms) are precisely those that should be making financing choices according to the pecking order. Growth firms in the manufacturing sector of the LQ45 Index should face more asymmetric information in capital markets and be less watched by the analysts. B. Mature Firms Our regression model results of financing deficit on net debt issue, net equity issue, and newly retained earning for mature firms are as follow. Regression Model Result 141

142 As for growth firms, the regression model of mature firms, Y is net debt issued and deficit is the financing deficit. This deficit is financed with debt and/or equity. If firms follow the pecking order, changes in debt should track changes in the deficit one-for-one. Therefore, the expected coefficient on the deficit is 1. Net Debt Issue From the tables we can conclude that the financing deficit has positive significant effects on net debt issue with t-value of and significance value of This result suggests that high deficit firms would tend to issue more net debt. However, the coefficient on the deficit is and constant value is Net Equity Issue The financing deficit has positive significant effects on net equity issue with t-value of and significance value of This result suggests that high deficit firms would tend to issue more net equity. However, the coefficient on the deficit is and the constant value is Newly Retained Earning The financing deficit has negative significant effects on newly retained earning with t- value of and significance value of This result suggests that high deficit firms would not tend to use newly retained earning. However, the coefficient on the deficit is and constant value is Augmented Model Result If firms are issuing equity first and debt is the residual source of financing, then this relationship should be convex and the coefficient on the squared deficit term would be positive. However, our result shows a negative coefficient on the squared deficit term, it implies that firms are limited by their debt capacity constraints and they have to resort to issuing equity. A squared deficit coefficient that is large in absolute value implies a greater reliance on equity finance for larger values of the financing deficit. Prefer External or Internal Financing? The coefficient of financing deficit on newly retained earning is negative for growth and mature firms. The coefficient of financing deficit on net debt and net equity issue are positive significant for growth and mature firms. For both firms, the significance value of net debt issue is more significant than net equity issue. The evidence seems to suggest mature and growth firms rely more heavily on external financing. Prefer Debt or Equity? Growth firms have the same significantly value with mature firms while growth firms have higher standardised coefficients (0.385) of deficit on net debt issue than mature firms (0.383), however mature firms have higher standardised coefficients (0.254) of deficit on net equity issue than of growth firms (0.177). These results imply that deficit of mature firms is solved more by net equity issue while deficit of growth firms is solved more by net debt issue. 142

143 From augmented model result, the findings are consistent with the firms following the pecking order: the coefficient on the deficit is positive and the coefficient on the deficit-square is negative. Both growth and mature firms are issuing debt first, while equity is the residual source of financing once they reach their debt capacities. Our evidence seems to suggest mature and growth firms rely more heavily on debt financing rather than equity financing. For growth firms, Adjusted R Square (0.273) and R Square (0.285) are stronger than mature firms (0.229) and (0.245). R-squared of financing deficit on net debt issue of growth firms are higher than mature firms, while R-squared of financing deficit on net equity issue of mature firms are higher than of growth firms. Therefore, overall, we find that the pecking order theory describes the financing patterns of growth firms better than mature firms. Adjusted R-squared of predictors of financing deficit and the financing deficit square on net debt issue of growth firms (0.273) are higher than mature firms (0.229). It implies that financing deficit and financing deficit square on net debt issue of growth firms rely more on net debt issue. Therefore, the pecking order theory describes the financing patterns of growth firms better than mature firms, as mature firms are more closely followed by analysts and are better known to investors, and hence, should suffer less from problems of information asymmetry. The results are consistent with firms following the pecking order: the coefficient on the deficit is positive and the coefficient on the deficit square is negative. Both growth and mature firms are issuing debt first, while equity is the residual source of financing once they reach their debt capacities. Comparing across life cycle stages however, we found that growth firms have significantly higher debt-deficit sensitivities indicating that growth firms follow the pecking order more closely. This is consistent to conventional wisdom since they would expect growth firms to suffer more from information asymmetry problems. This result is not in line with the finding research of Bulan and Yan (2009). Older and more mature firms are more closely followed by analysts and are better known to investors, and hence, should suffer less from problems of information asymmetry. For example, a good reputation (such as a long credit history) mitigates the adverse selection problem between borrowers and lenders. Thus, mature firms are able to obtain better loan rates compared to their younger firm counterparts (Diamond, 1989). Furthermore, mature firms generally have more internal funds due to higher profitability and lower growth opportunities. Older, more stable and highly profitable firms with few growth opportunities and good credit histories are more suited to use internal funds first, and then debt before equity for their financing needs. As explained by the pecking order theory, firms with the greatest information asymmetry problems (specifically young growth firms) are precisely those that should be making financing choices based on the pecking order. Thus, they are more suited to use internal funds first, and then debt before equity for their financing needs. From descriptive statistics and correlation matrix, we conclude that: growth firms have lower newly retained earning and lower profitability. It is indicated by profitability and newly retained earning which have positive significant correlation (0.654; 0.000). It suggests that the larger the firm s profitability, the higher the firm s newly retained earning. Small-growth firms issue more net debt to solve financing deficit than equity as they have higher asset tangibility to secure net debt issue. It was shown by tangibility and financing deficit have positive significant correlation (0.551; 0.000) which implies that firm that has higher 143

144 financing deficit has larger asset tangibility to secure debt issue. Tang and newly retained earning are negative significant correlated (-0.227; 0.001), it implies that the lower the firm s newly retained earning the larger the firm s tangibility. However, growth-small firms have higher profitability than mature-large firms. It shown by profitability and asset tangibility which have negative significant correlation and size and asset tangibility have positive significant correlation, profitability and risk have negative significant correlation. Hence, small-growth firms have low risk (earning volatility). Even though growth firms have higher financing deficit, financing deficit square, net equity issued, but they finance their financing deficit with more net debt issue than net equity issue, while mature firms have higher net debt issued, but they manage their financing deficit with more net equity issue than net debt issue. For growth firms, long-term leverage and capital expenditure have higher composition in forming financing deficit, while for mature firms dividend and working capital have higher composition in forming financing deficit as mature firms have higher newly retained earning. Mature firms have higher dividend, working capital, cashflow, newly retained earning, net debt issued, while growth firms have higher long-term leverage, fixed asset, financing deficit, financing deficit1square, net equity issued (descriptive statistics). Growth firms have lower profitability, higher tangibility, higher risk, while mature firms have higher profitability, lower tangibility, lower risk (correlation matrix). It can be shown that there exists positive significant correlation (0.654; 0,000) between profitability and newly retained earning. The larger the firm s profitability, the higher the firm s newly retained earning. Profitability and financing deficit are significantly negative (-0.461; 0.000). It suggests that the larger the firm s profitability, the smaller the firm s financing deficit. Tangibilty and financing deficit are significantly positive (0.551; 0.000). It implies that the larger the firm s tangibility, the higher the firm s financing deficit. Tangibility and newly retained earning are significantly negative (-0.227; 0.001). It implies that the larger the firm s tangibility, the lower the firm s financing deficit. Risk and newly retained earning are significantly negative (-0.444; 0.000). It implies that the larger the firm s risk, the lower the firm s newly retained earning. According to Myers (1984), a firm is said to follow a pecking order if it prefers internal to the external financing and debt to equity if external financing is used. Therefore, overall, we found that the pecking order theory described the financing patterns of growth firms better than mature firms, as mature firms were more closely followed by analysts and were better known to investors, and hence, should suffer less from problems of information asymmetry. Our result is consistent from the theory, and also consistent from the previous research findings of Shyam-Sunder and Myers (1999). They proposed a direct test of the pecking order and found strong support for the theory among a sample of large firms. However, some empirical evidence for the pecking order theory over firms life cycles which are inconsistent with our results are as follow: The plausible explanation is that the Indonesian economy and market conditions differ from those under which the previous research was developed, such as the USA. More recent work by Lemmon and Zender (2004) and Agca and Mozumdar (2004) have shown that the Shyam-Sunder and Myers test did not account for a firm s debt capacity; a 144

145 constraint that was particularly binding for small firms. Thus, it was not surprising that this test failed to find support for the pecking order among small firms. To address this shortcoming, Lemmon and Zender and Agca and Mozumdar used sub-samples of firms that were the least debtconstrained and they found support for the pecking order. In addition, once debt capacity constraints were accounted for, they found that the pecking order performed well even for small firms. Frank and Goyal (2003), found that large firms fitted the pecking order theory better than of small firms, contrary to the predictions of the theory. Frank and Goyal (2003) examined the broad applicability of the pecking order theory. Their evidence was based on a large cross-section of US publicly traded firms over long time periods. It showed that external financing was heavily used by some firms. On average net equity issued track the financing deficit more closely than did net debt issues. These facts did not match the claims of the pecking order theory. The greatest support for pecking order was found among large firms, which might be expected to face the least severe adverse selection problem since they received much better coverage by equity analysts. Even here, the support for pecking order was declining over time and the support for pecking order among large firms was weaker in the 1990s. They concluded that the pecking order theory did not explain broad patterns in the data. Overall, Bulan and Yan (2007) found that the pecking order theory described the financing patterns of mature firms better than of growth firms. This is contrary to the theory s prediction that firms with the greatest information asymmetry problems (specifically young, growth firms) are precisely those that should be making financing choices according to the pecking order. These results are robust under alternative empirical models for testing the pecking order theory. Bulan and Yan (2007) further saw that growth firms had larger financing deficits, as expected. The financing deficit is defined as the uses of funds minus internal sources of funds, which, by an accounting identity, is also the sum of net debt issued and net equity issued. There seems to be no difference in net debt issued between the two cohorts, while net equity issued is larger for the growth firms. From this simple comparison, the evidence seems to suggest growth firms rely more heavily on equity financing rather than debt. This finding is consistent with Agca and Mozumdar (2004) and Lemmon and Zender (2004). Bulan and Yan (2009) examined the central prediction of the pecking order theory of financing among firms in two distinct life cycle stages, namely growth and maturity. They found that within a life cycle stage, where levels of debt capacity and external financing needs were more homogeneous, and after sufficiently controlling for debt capacity constraints, firms with high adverse selection costs followed the pecking order more closely. Financing deficit of growth firms are higher than financing deficit of mature firms, as growth firms have lower cashflow than mature firms. Additionally, the findings that growth firms had greater financing deficits but smaller debt capacities are implying that growth firms would reach their debt capacities more often than mature firms. The results are consistent with firms following the pecking order: the coefficient on the deficit is positive and the coefficient on the deficit square is negative. Both growth and mature firms issued debt first, while equity is the residual source of financing once they reach their debt capacities. Comparing across life cycle stages however, they found that mature firms had significantly higher debt-deficit sensitivities indicating that mature firms followed the pecking order more closely. That was contrary to conventional wisdom, since they would expect growth firms to suffer more from information asymmetry problems. Bulan and Yan (2009) documented 145

146 this result as a maturity effect in firm financing choice. Mature firms are older, more stable, and highly profitable with few growth opportunities and good credit histories. Hence, they are able to borrow more easily and at a lower cost. Therefore, by the very nature of their life cycle stage, mature firms are pre-disposed to utilising debt financing first before equity. Halov and Heider s (2003) main hypothesis was that firms issued more equity and less debt in situations where risk was an important element of the adverse selection problem of outside financing. They found robust empirical support for the hypothesis and documented a strong link between asset risk and the decision to issue debt and equity in a large unbalanced panel of publicly traded US firms from 1971 to Frank and Goyal expected the pecking order to work best for young, small firms since they argued that these firms should have the most severe asymmetric information problem. Halov and Heider (2003) explained that the standard pecking order should not work at all for those firms. Risk differences, i.e. differences in failure rates and upside potential, play an important role in the adverse selection problem for young, small firms. Hence, they should issue equity and not debt, or alternatively, rational investors demand equity and not debt from these firms. Therefore, our result is what we expected Analysis of Results and Its Consistency to the Theory and Previous Research (Small and Large Firms) As shown by table 6.17, the regression result for large and small firms is as follows: The financing deficit is financed with debt and/or equity. If firms follow the pecking order, changes in debt should track changes in the deficit one-for-one. Therefore, the expected coefficient on the deficit is 1. Table Regression Results for Large and Small Firms Coefficients a Model Unstandardised Coefficients Standardised Coefficients T Sig. Collinearity Statistics B Std. Beta Toleran VIF Error ce 1 (Constant) FD_L a. Dependent Variable: NDEBT_L F-value=0.837 (0.373) ; R-Squared=0.047 ; N=19 1 (Constant) FD_L a. Dependent Variable: NEQUITY_L F-value= (0.004) ; R-Squared=0.393 ; N=19 1 (Constant) FD_L a. Dependent Variable: NRE_L F-value= (0.001) ; R-Squared=0.464 ; N=19 1 (Constant) FD_S

147 a. Dependent Variable: NDEBT_S F-value=9.296 (0.028) ; R-Squared=0.650 ; N=7 1 (Constant) FD_S a. Dependent Variable: NEQUITY_S F-value=1.149 (0.333) ; R-Squared=0.187 ; N=7 1 (Constant) FD_S a. Dependent Variable: NRE_S F-value=1.829 (0.234) ; R-Squared=0.268 ; N=7 A. Large Firms Our regression model results of financing deficit on net debt issue, net equity issue, and newly retained earning for large firms are as follow: Net Debt Issue From the tables we can conclude that the financing deficit has positive insignificant effects on net debt issue with t-value of and significance value of This result suggests that large firm with high financing deficit would tend to issue more net debt. However, the coefficient on the deficit is and constant value is Net Equity Issue The financing deficit has positive significant effects on net equity issue with t-value of and significance value of This result suggests that large firm with high deficit financing would tend to issue more net equity. However, the coefficient on the deficit is and constant value is Newly Retained Earning The financing deficit has negative significant effects on newly retained earning with t- value of and significance value of This result suggests that large firm with high deficit financing would not tend to use newly retained earnings to finance the deficit. However, the coefficient on the deficit is and constant value is B. Small Firms Our regression model results of financing deficit on net debt issue, net equity issue, and newly retained earning for small firms are as follow: Net Debt Issue From the tables we can conclude that the financing deficit has positive significant effects on net debt issue with t-value of and significance value of This result suggests that small firm with high financing deficit would tend to issue more net debt. However, the coefficient on the deficit is and constant value is

148 Net Equity Issue The financing deficit has positive insignificant effects on net equity issue with t-value of and significance value of This result suggests that small firm with high financing deficit would tend to issue more net equity. However, the coefficient on the deficit is and constant value is Newly Retained Earning The financing deficit has negative insignificant effects on newly retained earning with t- value of and significance value of This result suggests that small firms with high deficit of financing would not tend to use newly retained earnings to finance the deficit. However, the coefficient on the deficit is and constant value is Our result implies that the deficit of large firms is solved more by net equity issue, while the deficit of small firms is solved more by the net debt issue. It is consistent with the pecking order theory which predicts an inverse relation between leverage and firm size. The argument is that large firms have been around longer and are better known. Thus, large firms face lower adverse selection and can more easily issue equity compared to small firms where adverse selection problems are severe. Large firms also have more assets and thus the adverse selection may be more important if it impinges on a larger base. Rajan and Zingales (1995) argued that there was less asymmetrical information about the larger firms. This reduced the chances of undervaluation of the new equity issue and thus encouraged the large firms to use equity financing Analysis of the Indonesian Condition From the results, we imply that our growth and mature firms in the manufacturing sector of the LQ45 Index prefers external to internal financing and debt to equity if external financing is used. Therefore, both kinds of firms are following the pecking order theory. Specifically, the results imply that deficit of mature firms is solved more by net equity issue while deficit of growth firms is solved more by net debt issue. Following the pecking order theory, growth firms should face more asymmetric information in capital markets. However, in the Indonesian capital market namely IDX, information asymmetry both for growth and mature firms has rarely happened as the government of Indonesia has stipulated the regulations regarding information asymmetry. The efforts of the Government are as follow: (a) Develop protection scheme of investor. Investor confidence in capital markets is in absolute terms that must be constantly guarded by the regulator. Investors will utilise the capital markets industry as a means of investment and risk management if they feel confident that their interests are protected. (b) Improving the quality of financial information transparency in capital market industry. In the Indonesian capital markets industry, the transparency of financial information is one form of implementation of the disclosure of information. Investment decision made by investors will be strongly influenced by the information obtained from financial statements Capital Structure over Firm s Life Cycle The following graphics are to describe which firms life cycles, namely mature/growth firms, small/large firms, and old/young firms in the manufacturing sector raise relatively more (or less) capital externally (or internally) than other firms life cycles in the manufacturing sector. 148

149 Figure 6.7. Mature Firms Mature Firms Figure 6.8. Growth Firms Growth Firms 0,5 0,5 0,4 0,4 0,3 0,3 0,2 0,2 0,1 0,1 0 FD1 NDEBT NEQUITY NRE 0 FD1 NDEBT NEQUITY NRE Figure 6.9. Large Firms Large Firms Figure Small Firms Small Firms 0,5 0,4 0,3 0,6 0,4 0,2 0,1 0 FD1 NDEBT NEQUITY NRE 0,2 0 FD1 NDEBT NEQUITY NRE 149

150 Figure Young Firms Figure Old Firms 0,35 0,3 0,25 0,2 0,15 0,1 0,05 0 Young Firms 0,6 0,5 0,4 0,3 0,2 0,1 0 Old Firms FD1 NDEBT NEQUITY NRE Figure Mature-Growth Firms Figure Large-Small Firms 0,5 0,4 0,3 0,2 0,1 0 Mature Growth 0,5 0,45 0,4 0,35 0,3 0,25 0,2 0,15 0,1 0,05 0 Large Firms small firms 150

151 Old Firms Young Firms Large Firms Small firms Mature Firms Growth Firms Figure Young-Old Firms Figure All Classification of Firms 0,6 0,5 0,4 0,3 0,2 0,1 0 0,6 0,4 0,2 0 FD1 NDEBT NEQUITY NRE Old Firms Young Graphics show that large and small firms in the manufacturing sector raise relatively more capital externally than internally, and they raise more equity than debt. Young firms in the manufacturing sector raise relatively more NRE than equity and debt, however, they raise more equity than debt. Old firms in the manufacturing sector raise relatively more capital externally than internally, and they raise more debt than equity. Mature and growth firms in the manufacturing sector raise relatively more capital externally than internally, and they raise more debt than equity. However, from this result, we have not concluded yet whether mature or growth firms that more rely on debt and equity. Therefore, we test it through hypothesis 4 which gives a more specific result. Young firms in the manufacturing sector raise a higher capital internally than the other types of firms and are followed by small firms. Large firms in the manufacturing sector raise a lower capital internally than the other types of firms and are followed by old firms. Small firms in the manufacturing sector raise a higher net debt than the other types of firms and are followed by old and mature firms. Young firms in the manufacturing sector raise a lower net debt than the other types of firms and are followed by large firms. Small firms in the manufacturing sector raise a higher net equity than the other types of firms and are followed by young firms. Mature firms in the manufacturing sector raise a lower net equity than the other types of firms and are followed by large firms. Old firms in the manufacturing sector have a higher financing deficit in all other types of firms and are followed by large firms. Young firms in the manufacturing sector have a lowest financing deficit in all other types of firms and are followed by mature firms Frequency Frequency tables consist of mean, median, mode, deviation, variance, skewness, standard error of skewness, kurtosis, standard error of kurtosis, range, maximum, minimum, sum, percentiles 25, 50, and 75. These values describe the tendency of variables. The meaning of each value is as follow. 151

152 The mode of a set of data values is the value (s) that occurs most often. The median of a set of data values is the middle value of the data set when it has been arranged in ascending order. That is, from the smallest value to the highest value. The mean (or average) of a set of data values is the sum of all of the data values divided by the number of data values. Standard deviation is a widely used measurement of variability or diversity used in statistics. It shows how much variation or "dispersion" there is from the average (mean, or expected value). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data are spread out over a large range of values. In descriptive statistics, the range is the length of the smallest interval which contains all the data. It is calculated by subtracting the smallest observation (sample minimum) from the greatest (sample maximum) and provides an indication of statistical dispersion. The variance is used as a measure of how far a set of numbers are spread out from each other. It is one of several descriptors of a probability distribution, describing how far the numbers lie from the mean (expected value). Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable. The skewness value can be positive or negative, or even undefined. Qualitatively, a negative skew indicates that the tail on the left side of the probability density function is longer than the right side and the bulk of the values (possibly including the median) lie to the right of the mean. A positive skew indicates that the tail on the right side is longer than the left side and the bulk of the values lie to the left of the mean. A zero value indicates that the values are relatively evenly distributed on both sides of the mean, typically but not necessarily implying a symmetric distribution. Kurtosis is a measure of the "peakedness" of the probability distribution of a real-valued random variable, although some sources are insistent that heavy tails, and not peakedness, is what is really being measured by kurtosis. Higher kurtosis means more of the variance is the result of infrequent extreme deviations, as opposed to frequent modestly sized deviations. Sum is the amount of the values. Minimum is the minimum value. Maximum is the maximum value. Table 6.18, 6.19, 6.20, 6.21, 6.22, and 6.23 show the frequency of mature-growth, largesmall, and old-young firms which analyse the mean, median, mode, deviation, variance, skewness, standard error of skewness, kurtosis, standard error of kurtosis, range, maximum, minimum, sum, and percentiles 25, 50, and 75. Table Frequency of Mature Firms FD_M NRE_M NEQUITY_M NDEBT_M N Valid Missing Mean Median Mode a a a Std. Deviation Variance Skewness Std. Error of Skewness Kurtosis Std. Error of Kurtosis Range Minimum Maximum

153 Sum Percentiles Table Frequency of Growth Firms FD_G NRE_G NEQUITY_G NDEBT_G N Valid Missing Mean Median Mode a a a Std. Deviation Variance Skewness Std. Error of Skewness Kurtosis Std. Error of Kurtosis Range Minimum Maximum Sum Percentiles For financing deficit variable of mature and growth firms, mean, median, sum, percentiles 25, 50, and 75 of mature firms are lower than of growth firms. For financing deficit variable of mature and growth firms, mode, standard deviation, variance, skewness, standard error of skewness, kurtosis, standard error of kurtosis, range, minimum, and, maximum of mature firms are higher than of growth firms. For net debt issue variable of mature and growth firms, mode, skewness, standard error of skewness, standard error of kurtosis, minimum, percentiles 25 of mature firms are higher growth firms. For net debt issue variable of mature and growth firms, mean, median, standard deviation, variance, kurtosis, range, maximum, sum, percentiles 50, and 75 of mature firms are lower than of growth firms. For net equity issue variable of mature and growth firms, mode and percentiles 25 of mature firms are exactly the same with growth firms. For net equity issue variable of mature and growth firms, standard error of skewness, kurtosis, standard error of kurtosis, and minimum of mature firms are higher than of growth firms. For net equity issue variable of mature and growth firms, mean, median, standard deviation, variance, skewness, range, maximum, sum, percentiles 50, and 75 of mature firms are lower than of growth firms. 153

154 For newly retained earning variable of mature and growth firms, standard deviation, variance, kurtosis, and range of mature firms are lower than of growth firms. For newly retained earning variable of mature and growth firms, mean, median, mode, skewness, standard error of skewness, standard error of kurtosis, minimum, maximum, sum, percentiles 25, 50, and 75 of mature firms are higher than of growth firms. Table Frequency of Large Firms Statistics FD_L NDEBT_L NEQUITY_ NRE_L L N Valid Missing Mean Std. Error of Mean Median Mode.07 a -.26 a.00 a -.08 a Std. Deviation Variance Skewness Std. Error of Skewness Kurtosis Std. Error of Kurtosis Range Minimum Maximum Sum Percentiles a. Multiple modes exist. The smallest value is shown Table Frequency of Small Firms Statistics FD_S NDEBT_S NEQUITY_ NRE_S S N Valid Missing Mean Median Mode.18 a -.05 a -.03 a.02 a Std. Deviation Variance Skewness Std. Error of Skewness Kurtosis Std. Error of Kurtosis

155 Range Minimum Maximum Sum Percentiles a. Multiple modes exist. The smallest value is shown For financing deficit variable of large and small firms, mean, median, sum, percentiles 25, 50, and 75 of large firms are higher than of small firms. For financing deficit variable of large and small firms, mode, standard deviation, variance, skewness, standard error of skewness, kurtosis, standard error of kurtosis, range, minimum, and maximum of large firms are lower than of small firms. For net debt issue variable of large and small firms, variance of large firms is exactly the same with small firms, while standard deviation, kurtosis, range, and sum of large firms are higher than of small firms. For net debt issue variable of large and small firms, mean, median, mode, skewness, standard error of skewness, standard error of kurtosis, minimum, maximum, and percentiles 25, 50, and 75 of large firms are lower than of small firms. For net equity issue variable of large and small firms, mode, skewness, kurtosis, minimum, and sum of large firms are higher than of small firms. For net equity issue variable of large and small firms, mean, median, standard deviation, variance, standard error of skewness, standard error of kurtosis, range, maximum, percentiles 25, 50, and 75 of large firms are lower than of small firms. For newly retained earning variable of large and small firms, range of large firms are higher than of small firms. For newly retained earning variable of large and small firms, mean, median, mode, standards deviation, variance, skewness, standard error of skewness, kurtosis, standard error of kurtosis, minimum, maximum. Sum, percentiles 25, 50, and 75 of large firms are lower than of small firms. Table Frequency of Old Firms Statistics FD_O NDEBT_O NEQUITY_O NRE_O N Valid Missing Mean Median Mode.07 a -.26 a.00 a -.08 a Std. Deviation Variance Skewness Std. Error of Skewness Kurtosis Std. Error of

156 Kurtosis Range Minimum Maximum Sum Percentiles a. Multiple modes exist. The smallest value is shown Table Frequency of Young Firms Statistics FD_Y NDEBT_Y NEQUITY_Y NRE_Y N Valid Missing Mean Median Mode.28 a -.05 a -.03 a.06 a Std. Deviation Variance Range Minimum Maximum Sum Percentiles a. Multiple modes exist. The smallest value is shown For financing deficit variable of old and young firms, mean, median, standard deviation, variance, skewness, standard error of skewness, kurtosis, standard error of kurtosis, range, maximum, sum, percentiles 50 and 75 of old firms are higher than of young firms, while for financing deficit variable of old and young firms, mode, minimum, and percentiles 25 of old firms are lower than of young firms, For net debt issue variable of old and young firms, mean, median, skewness (-), standard error of skewness, kurtosis, standard error of kurtosis, range, maximum, sum, percentiles 25, 50, and 75 of old firms are higher than of young firms. For net debt issue variable of old and young firms, mode, standard deviation, variance, and minimum of old firms are lower than of young firms. For net equity issue variable of old and young firms, mean, median, standard deviation, variance, range, maximum, percentiles 50, and 75 of old firms are lower than of young firms. For net equity issue variable of old and young firms,mode, skewness, standard error of skewness, kurtosis, standard error of kurtosis, minimum, sum, and percentiles 25 of old firms are higher than of young firms. 156

157 For newly retained earning variable of old and young firms, mean, median, mode, standard deviation, variance, minimum, maximum, percentiles 25,50, and 75 of old firms are lower than of young firms. For newly retained earning variable of old and young firms, skewness, standard error of skewness, kurtosis, standard error of kurtosis, range, and sum of old firms are higher than of young firms Statistical Power Analysis of Hypotheses 1, 2, 3, and 4 To examine to what extent the theory is implied in our sample, we also analyse the predictive power of the result. It consists of analysing the un-standardised beta coefficients, the standardised beta coefficients, analysis of variance (ANOVA), coefficient of determination (Rsquared), and descriptive statistics. A. The Un-standardised Beta Coefficients B is the value for the regression equation for predicting the dependent variable from the independent variable. These are called un-standardised coefficients because they are measured in their natural units. As such, the coefficients cannot be compared with one another to determine which one is more influential in the model, because they can be measured on different scales. For hypothesis 1, (Constant) value of profitability, growth, tangibility, risk, and size on short-term leverage as dependent variable is 0.138, B Coefficients of profitability, growth, tangibility, risk, and size are , , 0.012, 1.218, and (Constant) value of profitability, growth, tangibility, risk, and size on long-term leverage as dependent variable is 0.141, B Coefficients of profitability, growth, tangibility, risk, and size are , 0.372, , , and (Constant) value of profitability, growth, tangibility, risk, and size on total leverage as dependent variable is 0.207, B Coefficients of profitability, growth, tangibility, risk, and size are , 0.104, 0.014, 0.506, and (Constant) value of profitability, growth, tangibility, risk, and size on market leverage as dependent variable is 1.283, B Coefficients of profitability, growth, tangibility, risk, and size are , 0.106, , 0.142, and From these results, we can conclude that the highest value is market leverage while the lowest is longterm leverage. For hypothesis 2, each model for firms sample have only one predictor variable, then beta is equivalent to the correlation coefficient between the predictor and the criterion variable. The following is the result of (constant) value and beta coefficients of financing deficit on net debt issued, net equity issued, and newly retained earning for all of sample of firms. (Constant) value of financing deficit on net debt issued is 0.001, B coefficients of financing deficit is It indicates that if there is no financing deficit, then net debt issued is If value of financing deficit 1 is 1, then net debt issued is (Constant) value of financing deficit on net equity issued is , B coefficients of financing deficit is It indicates that if there is no financing deficit, then net equity issued is If value of financing deficit is 1, then net equity issued is (Constant) value of financing deficit on newly retained earning is 0.086, B coefficients of financing deficit is It indicates that if there is no financing deficit, then newly retained earning is If value of financing deficit is 1, then newly retained earning is (Constant) value of financing deficit on repurchase equity is , B coefficients of financing deficit is It indicates that if there is no financing deficit, then repurchase equity is If value of financing deficit is 1, then repurchase equity is From these results, we can conclude that the highest value is net debt issue. It indicates that if firms face financing deficit, they tend to issue more debt. 157

158 For hypothesis 3, (constant) value of net debt issued on the monthly and the yearly stock price is positive. From the table in the appendix, we can conclude that the highest value is the January stock price while the lowest value is the September stock price. (Constant) value of net equity issued on monthly and yearly stock price is positive while net equity issued is negative. (Constant) value of repurchase equity on monthly and yearly stock price is positive but not significant. For hypothesis 4, the result of (constant) value and beta coefficients of financing deficit on net debt issued, net equity issued, and newly retained earning for growth and mature firms is as follows. For growth firms, (constant) value of financing deficit on net debt issue is , beta coefficients of financing deficit are It indicates that if there is no financing deficit, then net debt issue is , if value of financing deficit is 1, then net debt issue is (Constant) value of financing deficit on net equity issue is 0.021, beta coefficients of financing deficit is 0.073, it indicates that if there is no financing deficit, then net equity issue is 0.021, if value of financing deficit is 1, then net equity issue is (Constant) value of financing deficit on newly retained earning is 0.057, beta coefficients of financing deficit are It indicates that if there is no financing deficit, then newly retained earning is 0.057, if value of financing deficit is 1, then newly retained earning is For mature firms, (constant) value of financing deficit on net debt issue is 0.026, beta coefficients of financing deficit is It indicates that if there is no financing deficit, then net debt issue is If value of financing deficit is 1, then net debt issue is (Constant) value of financing deficit on net equity issue is , B coefficients of financing deficit1 is It indicates that if there is no financing deficit, then net equity issue is If value of financing deficit is 1, then net equity issue is (Constant) value of financing deficit on newly retained earning is 0.074, beta coefficients of financing deficit are It indicates that if there is no financing deficit, then newly retained earning is If value of financing deficit is 1, then newly retained earning is B. The Standardised Beta Coefficients Beta(s) are the standardised coefficients. These are the coefficients that we would obtain if we standardised all of the variables in the regression, including the dependent and all of the independent variables, and ran the regression. By standardising the variables before running the regression, we have put all of the variables on the same scale, and we can compare the magnitude of the coefficients to see which one has more of an effect. We will also notice that the larger betas are associated with the larger t-values. The standardised beta coefficients give a measure of the contribution of each variable to the model. A large value indicates that a unit change in this predictor variable has a large effect on the criterion variable. For hypothesis 1, standardised beta coefficients of profitability, growth, tangibility, risk, and size on short-term leverage, long-term leverage, total leverage, market leverage are as follow: standardised coefficients of profitability, growth, tangibility, risk, and size on short-term leverage as dependent variable are , , 0.071, 0.346, and Standardised coefficients of profitability, growth, tangibility, risk, and size on long-term leverage as dependent variable are , 0.364, , , and Standardised coefficients of profitability, growth, tangibility, risk, and size on total leverage as dependent variable are , 0.093, 0.090, 0.151, and Standardised coefficients of profitability, growth, tangibility, risk, and size on market leverage as dependent variable are as follow: , 0.109, , 0.049, and

159 For hypothesis 2, the result of the standardised beta coefficients of financing deficit on net debt issued, net equity issued, and newly retained earning for all samples of firms is explained as follows. Standardised coefficients of financing deficit (the predictor) on net debt issued the (criterion) is Standardised coefficients of financing deficit (the predictor) on net equity issued the (criterion) is Standardised coefficients of financing deficit (the predictor) on newly retained earning the (criterion) is Standardised coefficients of financing deficit (the predictor) on repurchase equity (criterion) is It is the same with the result of unstandardised beta coefficients, standardised coefficients of financing deficit on net debt issued is the highest. In other words the correlation coefficient between financing deficit on net debt issued is the strongest. It indicates that if firms face 1% financing deficit then they tend to issue 28.1% net debt and/or 16.9% net equity. For hypothesis 3, standardised coefficients of net debt issued on monthly and yearly stock price are positive, ranging from to From these results, we can conclude that the highest value is the January stock price while the lowest value is the December stock price. Standardised coefficients of net equity issued on monthly and yearly stock price are positive, ranging from to From these results, we can conclude that the highest value is the September stock price while the lowest value is the December stock price. Standardised coefficients of repurchase equity on monthly and yearly stock price are positive, ranging from to From these results, we can conclude that the highest value is the November stock price while the lowest value is the February stock price. For hypothesis 4, the result of the standardised beta coefficients of financing deficit on net debt issued, net equity issued, and newly retained earning for growth and mature firms is explained as follows. For mature firms, standardised coefficients of financing deficit 1 on its net debt issue is 0.383, it means that the correlation coefficient between the predictor and the criterion variable is Standardised coefficient of financing deficit on its net equity issue is It means that the correlation coefficient between the predictor and the criterion variable is Standardised coefficient of financing deficit on its newly retained earning is It means that the correlation coefficient between the predictor and the criterion variable is For growth firms, standardised coefficients of financing deficit 1 on net debt issue is 0.385, it means that the correlation coefficient between the predictor and the criterion variable is It is higher than mature firms. Standardised coefficient of financing deficit on net equity issue is It means that the correlation coefficient between the predictor and the criterion variable is It is lower than mature firms. Standardised coefficient of financing deficit of growth firms on its newly retained earning is It means that the correlation coefficient between the predictor and the criterion variable is It is more negative than mature firms. C. Analysis of Variance (ANOVA) The F-statistic will be calculated for analysis of variance (ANOVA) to test whether group population means are all equal or not. When the F-statistic is found significant, we may conclude that at least one of the population means of the groups differs from the others but ANOVA does not tell us which groups are different from which others (Bekiro, 2001). 159

160 For hypothesis 1, short-term leverage, long-term leverage, total leverage, market leverage as dependent variable and growth, tangibility, risk, size, and profitability as predictors, reaches statistical significance with F-value of and significant value of for short-term leverage, F-value of and significant value of for long-term leverage, F value of and significant value of for total leverage, F-value of and significant value of market leverage. Hence, the statistical significance as depicted in the ANOVA analysis (see table in appendix) indicates that the models of hypothesis 1 reach statistical significance less than 5%. For hypothesis 2, after reaching F-statistic result analysis of variance to test whether group population means are all equal or not, we did not find significant result for all models. F-value between net debt issued and financing deficit is with significance value of.000. F-value between net equity issued and financing deficit is with significance value of.000. F-value between newly retained earning and financing deficit is with significance value of.089. F-value between repurchase equity and financing deficit is with significance value of F-value between net debt issued and financing deficit is higher than F-value between net equity issued and financing deficit. From these results, the significance F-values obtained were between financing deficit and net debt issued and net equity issued, while F-values between financing deficit and newly retained earning and repurchase equity were not significant. For hypothesis 3, the statistical significance as depicted in the table of ANOVA shows that variable of issued debt from January to December did not yield statistical significance The statistical significance from January to December and yearly stock price became weaker. For hypothesis 4, for mature and growth firms, the statistical significance as shown in the ANOVA table in appendix indicates that the models for growth and mature firms reach statistical significance of less than 5%. For mature firms, F-value between net debt issue and financing deficit is with significance value of F-value between net equity issue and financing deficit is with significance value of For growth firms, F-value between net debt issue and financing deficit is (it is higher than mature firm) with significance value of F-value between net equity issue and financing deficit is (it is lower than mature firm) with significance value of D. Coefficient of Determination (R-squared) For hypotheses 1, R Squared (R 2 ) is the square of the measure of correlation and indicates the proportion of the variance in the criterion variable which is accounted for by our model. For hypotheses 1, we also see the adjusted R-square which attempts to yield a more honest value to estimate the R-squared for the population. When the number of observations is small and the number of predictors is large, there will be a much greater difference between R-square and adjusted R-square. By contrast, when the number of observations is very large compared to the number of predictors, the value of R-square and adjusted R-square will be much closer. R-squared for hypothesis 1 would be the value between short-term leverage, long-term leverage, total leverage, market leverage as dependent variable and growth, tangibility, risk, size, and profitability as predictors. 160

161 R-squared shows a predictor profitability, growth, tangibility, risk, and size of with short-term leverage as dependent variable. This means that 33.2% of the short-term leverage could be explained by the existence of those variables. The adjusted R-squared value of tangibility, growth, risk, size, and profitability as predictors for short-term leverage is These provide evidence that 31.4% of the short-term leverage could be explained by the existence of these predictors. R-squared shows a predictor profitability, growth, tangibility, risk, and size of with long-term leverage as dependent variable. This means that 28.8% of the long-term leverage could be explained by the existence of those variables. The adjusted R-squared value of tangibility, growth, risk, size, and profitability as predictors for long-term leverage is These provide evidence that 26.9% of the long-term leverage could be explained by the existence of these predictors. R-squared shows a predictor profitability, growth, tangibility, risk, and size of with total leverage as dependent variable. This means that 65.5% of the total leverage could be explained by the existence of those variables. The adjusted R-squared value of tangibility, growth, risk, size, and profitability as predictors for total leverage is These provide evidence that 64.6% of the total leverage could be explained by the existence of these predictors. R-squared shows a predictor of profitability, growth, tangibility, risk, and size of with market leverage as dependent variable. This means that 63.8% of the market leverage could be explained by the existence of those variables. The adjusted R-squared value of tangibility, growth, risk, size, and profitability as predictors for market leverage is These provide evidence that 62.9% of the market leverage could be explained by the existence of these predictors. Overall, there is no multicollinearity in the regression model of hypothesis 1. For hypothesis 2, R-squared would be the value between the financing deficit and net debt and net equity issue as dependent variables. For all sample of firms, R-squared shows a predictor financing deficit of 0.600, 0.215, with net debt issue, net equity issue, newly retained earning as dependent variables. This means that 60%, 21.5%, and 5.6% of the net debt issue, net equity issue, and newly retained earning could be explained by the existence of financing deficit. For all firms, R-squared shows a predictor financing deficit of with repurchase equity as dependent variables. This means that the repurchase equity almost cannot be explained by the existence of financing deficit. For augmented models, for all firms, adjusted R-squared shows a predictor financing deficit and financing deficit 1 square of (0.603) and with net debt issue as dependent variable. This means that 60.3% of the net debt issue can be explained by the existence of financing deficit and financing deficit square. R-squared of a predictor financing deficit with net debt issue as dependent variable is higher than net equity issue. This means that the percentage of the net debt issue can be explained more than net equity issue by the existence of financing deficit. For hypothesis 3, R-squared would be the correlation between the stock price and the net debt as dependent variables, the net equity and the debt issuance to repurchase equity as independent variable. 161

162 R-squared shows a predictor net debt issued between to and with monthly and yearly stock price as dependent variables. This means that 2.5% to 3.6%, and 0.1% of the monthly and yearly stock price could be explained by the existence of net debt issued. We can see that a predictor net debt issued on January stock price as dependent variables has the highest R-squared, while R-squared December stock price was the lowest. The R-squared of a predictor of net equity issuance on January to December ranged between to and the yearly stock price of as dependent variable. This means that between % and 0.4% of the increasing or decreasing of stock price could be explained by the existence of net equity issue. On September the R-squared got the highest figure, while in February, March, May, June, and December, it reached the lowest figure. For all firms, from January to December and yearly stock price, R-squared showed a predictor issue debt to repurchase equity of between and with the stock price as dependent variable. This means that between % and 13.0% of the increasing or decreasing of stock price could be explained by the existence of issue debt to repurchase equity. For all firms, R-squared shows a predictor issue debt to repurchase equity on the December stock price as dependent variables, has the highest R-squared, while R-squared of the February stock price has the lowest. For hypothesis 4, R-squared consists of the value for growth and mature firms. For mature firms, R-squared shows a predictor financing deficit of and with net debt issue and net equity issue as dependent variable. This means that 14.7% and 6.4% of the net debt issue and net equity issue could be explained by the existence of financing deficit. For growth firms, R-squared shows a predictor financing deficit of (it is higher than of mature firms) and (it is lower than of mature firms) with net debt issue and net equity issue as dependent variable. This means that 14.8% and 3.1% of the net debt issue and net equity issue could be explained by the existence of financing deficit. Therefore there is no multicollinearity in the regression model. For augmented models of mature firms, adjusted R-squared shows a predictor of financing deficit and financing deficit square of and with net debt issue as dependent variable. This means that 14.8% of the net debt issue could be explained by the existence of financing deficit and financing deficit square. For growth firms, adjusted R-squared shows a predictor financing deficit and financing deficit square of (it is higher than mature firm) and with net debt issue as dependent variable. This means that 14.8% of the net debt issue could be explained by the existence of financing deficit and financing deficit square. E. Descriptive Statistics For hypothesis 1, the average value of short-term leverage is while long-term leverage is , total leverage is and market leverage is The average value of tangibility, growth, risk, size, and profitability are , , , , and From these results, the highest average is market leverage. For hypotheses 2, the average value of each variable of hypothesis 2 for all samples of firms is as follows: The average value of net debt issued is while net equity issued is , and newly retained earning is The average value of financing deficit on net debt 162

163 issued, net equity issued, and newly retained earning is The average value of net debt issued is higher than net equity issued, hence if firms face financing deficit, they rely more heavily on debt than on equity (indicated by R 2, anova, and coefficient of regression). When firms issue debt to repurchase equity, the average of net debt issued to repurchase equity is , while the average of repurchase equity is negative The financing deficit they face is From this result we concluded that the average value of net debt issued is the highest. For variables of hypothesis 3, the monthly stock price is in the range of to with July as the highest while the lowest is October. Meanwhile, the yearly stock price is The average value of net equity is to , while the average value of repurchase equity is For hypothesis 4, descriptive statistics for variables of hypothesis 4 consist of average value of growth and mature firms. Net debt issue (0.0484) of growth firms (NDebt_G) is lower than net debt (0.0800) of mature firms (NDebt_M), while net equity issue of growth (NEquity_G) firms is higher than net equity issue of mature firms (NEquity_M) as growth firm has lower cashflow. The average value of financing deficit for the growth firms is while that of the mature firms is as mature firms has higher cashflow than growth firm. Even though growth firms issue more equity than mature firms, and mature firms issue more debt than growth firms, but when mature firms face financing deficit, they rely more heavily on equity while growth firms rely more heavily on debt. It indicated by R 2, anova, coefficient of regression and augmented. A mature firm has higher cash flow than a growth firm to secure the debt. Financing deficit of growth firms is higher than financing deficit of mature firms, as growing firms have lower cashflow than mature firms. Dividend (0.0026) of growing firms is lower than dividend (0.0554) of mature firms. Mature firms pay more dividend to shareholders as they have more cash flow to distribute to shareholders. Long-term leverage of growth firms is higher than long-term leverage (0.2029) of mature firms. Fixed asset (0.4664) of growth firms is higher than fixed asset (0.2815) of mature firms. dworking capital (0.0637) of growth firms is lower than dworking capital (0.1016) of mature firms. Cashflow (0.0277) of growth firms is lower than cashflow (0.0997) of mature firms. Newly retained earning (0.0075) of growth firms is lower than newly retained earning (0.0587) of mature firms Regression Assumptions of Hypotheses 1, 2, 3, and 4 Before analysing regression coefficients of variables, we must first make several assumptions about the population of the research. They represent an idealisation of reality, and as such, they are never likely to be entirely satisfied for the population in any real study (Van Horne, 1998). A good regression model should not have the following assumptions: 1. Multicollinearity The goal of the multicollinearity test of hypotheses 1, 2, 3, and 4 is to analyse whether there is correlation between variables. In our research, we test multicollinearity in the regression model by testing the correlation matrix (Ghozali, 2002), the tolerance values and VIF (Hair et al. 1998). Our results are as follow: 163

164 Correlations between Variables For hypothesis 1, the table gives details of the correlation between each pair of variables. We do not want strong correlations between the criterion and the predictor variables. The values here are acceptable. From the correlations matrix, it shows that there is no quite high correlation value (more than 0.90). Correlation coefficient between profitability and tangibility is with significant value of This is an indication that the higher/lower profitability the lower/higher tangibility. Correlation coefficient between profitability and size is with significant value of This is an indication that the higher/lower profitability the lower/higher size of the firm. Correlation coefficient between profitability and risk is with significant value of This is an indication that the higher/lower profitability the lower/higher risk. Correlation coefficient between profitability and growth is with significant value of This is an indication that the higher/lower profitability the lower/higher growth. Correlation coefficient between size and tangibility is with significant value of This is an indication that the higher/lower size, the higher/lower tangibility. Correlation coefficient between size and growth is with significant value of This is an indication that the higher/lower size the higher/lower growth. Correlation coefficient between risk and growth is with significant value of This is an indication that the higher/lower risk the higher/lower growth. From this result we concluded that multicollinearity does not exist in the regression model of hypothesis 1. For hypothesis 2, correlation between net debt and net equity issued and financing deficit are significantly positive, while correlation between newly retained earning and financing deficit are insignificantly negative. For firms, correlation between repurchase equity and financing deficit are insignificantly negative. For hypothesis 3, correlation between net debt and January-June stock price are significantly positive while correlation between net debt and July-December stock price are positive but not significant. Correlation between net equity and the yearly stock price or the price for each month during the year is negative but not significant. But if we compare with the repurchase equity, the stock price is positive but not significant. For hypothesis 4, the values here are acceptable. For mature and growing firms, correlation between net debt and net equity issue and financing deficit are positively significant. It indicates that the higher financing deficit the bigger the net debt and net equity issue. The Tolerance and Variance Inflation Factor (VIF) Value For hypothesis 1, the objective of analysing the tolerance values are to measure the correlation between the predictor variables which can vary between 0 and 1. The closer to zero the tolerance value is for a variable, the stronger the relationship between this and the other predictor variables. We should worry about variables that have a very low tolerance. SPSS will not include a predictor variable in a model if it has a tolerance of less that Meanwhile, variance inflation factor (VIF) value is an alternative measure of collinearity (in fact it is the reciprocal of tolerance) in which a large value indicates a strong relationship between predictor variables. For variables of hypothesis 1, short-term leverage, long-term leverage, total leverage, and market leverage as dependent variables and growth, tangibility, risk, size, and profitability as predictors, the tolerance values were also above the cut-off point 0.10 and the VIF values were below 10, indicating that multicollinearity was not a problem (Hair et al. 1998). 164

165 For variables of hypothesis 2, the tolerance values for net debt issued, net equity issued, newly retained earning, repurchase equity, financing deficit1 were above the cut-off point 0.10 and the VIF values were below 10. For variables of hypothesis 3, the tolerance values for net debt issued on monthly and yearly stock price were above the cut-off point 0.10 and the VIF values were below 10. While the tolerance values for net equity issued on monthly and yearly stock price were above the cut-off point 0.10, the VIF values were below 10. The tolerance values for issuing debt to repurchase equity on monthly and yearly stock price were above the cut-off point 0.10 and the VIF values were below 10. For variables of hypothesis 4, for mature and growing firms, the tolerance values for net equity issued, net debt issued, and financing deficit 1 were above the cut-off point 0.10 and the VIF values were below 10. Hence, from tolerance and VIF values of hypotheses 1, 2, 3, and 4 testing results indicate that multicollinearity was not a problem. 2. Autocorrelation For hypotheses 1, 2, 3, and 4, a test of autocorrelation aims to examine whether in a linear regression model has correlation between gadfly errors in the period t with an error in the period t-1 (before). One of the methods that we used to detect autocorrelation is the Durbin Watson (DW). DW value shows that there is no autocorrelation in the regression model. As a conservative rule of thumb, Field (2009) suggests that DW values less than 1 or greater than 3 are definitely cause for concern, however, values closer to 2 may still be problematic depending on the sample and model. For hypothesis 1, DW value between short-term leverage as dependent variable and predictors of growth, tangibility, risk, size, and profitability is For all firms, DW value between long-term leverage as dependent variable and predictors of growth, tangibility, risk, size, and profitability is For all firms, DW value between total leverage as dependent variable and predictors of growth, tangibility, risk, size, and profitability is For all firms, DW value between market leverage as dependent variable and predictors of growth, tangibility, risk, size, and profitability is A value greater than 2 indicates a negative correlation between adjacent residuals whereas a value below 2 indicates a positive correlation. For hypothesis 2, DW value between net debt issued, net equity issued, newly retained earning, repurchase equity were 1.667, 2.502, 1.494, and A value greater than 2 indicates a negative correlation between adjacent residuals whereas a value below 2 indicates a positive correlation. For hypothesis 3, DW value of predictor net debt issued and monthly stock price as dependent variables ranged from to DW value of predictor net debt issued and yearly stock price as dependent variable was A value greater than 2 indicated a negative correlation between adjacent residuals whereas a value below 2 indicated a positive correlation. For net equity issued, it ranged from to The DW value of predictor was The DW value of predictor for debt issuance to repurchase equity ranged from to The DW value for yearly stock price as dependent variable was For hypothesis 4, DW value of net debt and net equity issue and financing deficit are and For growing firms, DW value between net debt and net equity issue and financing deficit are and A value greater than 2 indicates a negative correlation 165

166 between adjacent residuals whereas a value below 2 indicates a positive correlation. Hence, for growing and mature firms, there are no DW values less than 1 or greater than 3 which definitely cause concern. 3. Heteroscedasticity Test of heteroscedasticity of hypotheses 1, 2, 3, and 4 aims to interpret whether the regression model has the differences residual variance from one observation to another observation (Ghozali, 2002). If the residual variance from one observation to another observation is the same, it is called homoscedasticity. The graphic of scatterplot (in appendix) shows that the dots have not established a specific pattern. Some of the dots located adjacent but some other dots spread above and below the numbers of 0 at the axis Y. Thus, data in the graphics exhibits homoscedasticity. 4. Normally Distributed From the result of testing hypotheses 1, 2, 3, and 4, to test the normal distribution that we can see from the graphics of histogram and normal P-P plot (in appendix), we concluded that the histogram gave the normal pattern of distribution. Meanwhile, the graphic of normal P-P plot shows that the dots spread around the diagonal line, and the spreading follows the diagonal line. Both of graphics show that the data meets reasonable assumption of normality. Therefore, based on the results of assumptions of population described above, the regression model does not have the assumptions of heteroscedasticity, multicollinearity, autocorrelation, and the data are normally distributed. Thus, our regression model is appropriate to use for testing the hypotheses 1, 2, 3, and Results of Panel Data Regression Analysis and the Comparison to Regression Analysis We applied mixed-effect linear regression to analyse longitudinal/panel data which reported both fixed effects and random effects. Panel data (also known as longitudinal or crosssectional time-series data) is a dataset in which the behaviour of entities is observed across time. Panel data allows us to control for variables we cannot observe or measure; or variables that change over time but not across entities with panel data we can include variables at different levels of analysis suitable for multilevel or hierarchical modeling. Two techniques use to analyse panel data are fixed effects and random effects. Hence, we use multilevel mixed-effect models to analyse our data with using mixed-effect linear regression so that we can report both fixed effects and random effects of the models. Fixed-effects are used whenever we are only interested in analysing the impact of variables that vary over time. Fixedeffects explore the relationship between predictor and outcome variables within an entity. Each entity has its own individual characteristics that may or may not influence the predictor variables. When using fixed-effects, we assume that something within the individual may impact or bias the predictor or outcome variables and we need to control for this. This is the rationale behind the assumption of the correlation between the entity s error term and predictor variables. Fixed-effects remove the effect of those time-invariant characteristics from the predictor variables so we can assess the predictors net effect. Another important assumption of the fixed-effects model is that those time-invariant characteristics are unique to the individual and should not be correlated with other individual characteristics. Each entity is different, therefore the entity s error term and the constant (which captures individual characteristics) should not be correlated with the others. If the error terms are 166

167 correlated then fixed-effects is not suitable since inferences may not be correct and we need to model that relationship (probably using random-effects). Meanwhile, the rationale behind the random effects model is that, unlike the fixed effects model, the variation across entities is assumed to be random and uncorrelated with the predictor or independent variables included in the model: the crucial distinction between fixed and random effects is whether the unobserved individual effect embodies elements that are correlated with the regressors in the model, not whether these effects are stochastic or not (Green, 2008). If we have reason to believe that differences across entities have some influence on our dependent variable then we should use random effects. An advantage of random effects is that we can include time invariant variables. Random effects assume that the entity s error term is not correlated with the predictors which allows for time-invariant variables to play a role as explanatory variables. In random-effects we need to specify those individual characteristics that may or may not influence the predictor variables. The problem with this is that some variables may not be available therefore leading to omitted variable bias in the model. Random-effects are allowed to generalise the inferences beyond the sample used in the model. Tables in appendix are our results of mixed-effect linear regression which reports both fixed effects and random effects for each hypothesis. Meanwhile, if we compare the results of regression and panel data regression, the following are the summary for each hypothesis and analysis. Table Summary of Panel Data Regression and Regression Results of Hypothesis 1 Variables Panel Data Regression Result Regression Result PRFT Negative significant Negative significant TANG Negative significant Negative significant SIZE Positive not significant Positive not significant RISK Positive significant Positive significant GROW Positive significant Positive significant Dependent variable: STL Variables Panel Data Regression Result Regression Result PRFT Negative significant Negative significant TANG Positive significant Positive significant SIZE Negative not significant Negative not significant RISK Negative not significant Negative significant GROW Positive significant Positive significant Dependent variable: LTL Variables Panel Data Regression Result Regression Result PRFT Negative significant Negative significant TANG Positive significant Positive not significant SIZE Positive not significant Positive not significant RISK Positive not significant Positive significant GROW Positive significant Positive significant Dependent variable: TLV Variables Panel Data Regression Result Regression Result PRFT Negative significant Negative significant TANG Positive significant Positive significant SIZE Positive not significant Negative not significant 167

168 RISK Positive not significant Positive not significant GROW Negative significant Negative significant Dependent variable: MRL For hypothesis 1, the results of regression and panel data regression are consistent for all variables except for SIZE on MRL. The influence of PRFT and TANG on STL are negative significant while the influence of RISK and GROW on STL are positive significant. However, the influence of SIZE on STL is positive but not significant. The influence of TANG and GROW on LTL are positive significant while the influence of PRFT on LTL are negative significant. However, the influence of SIZE on LTL is negative but not significant. The influence of RISK on LTL is negative. The influence of GROW on TLV is positive significant while the influence of PRFT on TLV is negative significant. However, the influence of SIZE on TLV is positive but not significant. The influence of TANG and RISK on TLV is positive. The influence of TANG on MRL is positive significant while the influence of PRFT and GROW on MRL are negative significant. However, the influence of RISK on MRL is positive but not significant. Table Summary of Panel Data Regression and Regression Results of Hypothesis 2 Variables Panel Data Regression Result Regression Result NDEBT Positive significant Positive significant NEQUITY Negative not significant Positive significant NRE Negative significant Negative not significant Independent variable: FD Variables Panel Data Regression Result Regression Result FD Positive significant Positive significant FDSQR Positive not significant Positive not significant Dependent variable: NDEBT Variables Panel Data Regression Result Regression Result FD Negative significant Negative not significant Dependent variable: REPO EQUITY For hypothesis 2, the results of regression and panel data regression are consistent for all variables except FD on NEQUITY. The influence of FD on NDEBT is positive significant while the influence of FD on NRE is negative significant from panel data regression, but not significant from regression result. However, the influence of FD on NEQUITY is negative insignificant from panel data regression, but positive significant from regression result. The influence of FD on NDEBT is positive significant while the influence of FDSQR on NDEBT is positive but not significant. Meanwhile, the influence of FD on REPOEQUITY is negative significant from panel data regression, but insignificant from regression result. Table Summary of Panel Data Regression and Regression Results of Hypothesis 3 Variables Panel Data Regression Result Regression Result NDEBT Positive not significant Positive not significant NEQUITY Negative not significant Negative not significant REPO EQUITY Positive significant Positive not significant 168

169 Dependent Variable: P_Yearly For hypothesis 3, the results of regression and panel data regression are consistent for all variables. The influence of NDEBT on P_Yearly is positive insignificant while the influence of NEQUITY on P_Yearly is negative insignificant. Meanwhile, the influence of REPOEQUITY on P_Yearly is positive significant from panel data regression, but positive insignificant from regression result. Table Summary of Panel Data Regression and Regression Results of Hypothesis 4 Variables Panel Data Regression Result Regression Result NDEBT_M Positive significant Positive significant NEQUITY_M Positive significant Positive significant NRE_M Negative significant Negative not significant Independent Variable: FD_M Variables Panel Data Regression Result Regression Result FD_M Positive significant Positive significant FDSQR_M Negative not significant Negative significant Dependent Variable: NDEBT_M Variables Panel Data Regression Result Regression Result NDEBT_G Positive significant Positive significant NEQUITY_G Positive significant Positive significant NRE_G Negative significant Negative significant Independent Variable: FD_G Variables Panel Data Regression Result Regression Result FD_G Positive significant Positive significant FDSQR_G Negative significant Negative significant Dependent Variable: NDEBT_G For hypothesis 4, for mature firms, the results of regression and panel data regression are consistent for all variables. The influence of FD on NDEBT and NEQUITY are positive significant while the influence of FD on NRE is negative significant from panel data regression, but not significant from regression result. The influence of FD on NDEBT is positive significant while the influence of FDSQR on NDEBT is negative significant from regression result, but not significant from panel data regression result. For hypothesis 4, for growth firms, the results of regression and panel data regression are consistent for all variables. The influence of FD on NDEBT and NEQUITY are positive significant while the influence of FD on NRE is negative significant. The influence of FD on NDEBT is positive significant while the influence of FDSQR on NDEBT is negative significant. 169

170 7. CONCLUSION 7.1. Conclusion Based on the results analysis of each hypotheses testing, overall, our conclusions are as follow: For hypothesis 1, profitability has a negative significant regression coefficient on shortterm leverage, long-term leverage, and total leverage. This suggests that highly profitability firms are less likely to use short-term leverage, long-term leverage, and total leverage, for financing their investments than the low profitability firms. Finally, profitability has a negative significant regression coefficient on market leverage. This suggests that highly profitability firms are less likely to use market leverage for financing their investments than the low profitability firms. Tangibility has a negative significant regression coefficient on short-term leverage, this suggests that highly tangibility firms are less likely to use short-term leverage for financing their investments than the low tangibility firms. Tangibility has a positive significant regression coefficient on long-term leverage; this suggests that highly tangibility firms are more likely to use long-term leverage for financing their investments than the low tangibility firms. Tangibility has a positive but not significant regression coefficient on total leverage, while tangibility has a positive significant regression coefficient on market leverage. This suggests that highly tangibility firms are more likely to use market leverage for financing their investments than the low tangibility firms. Size has a positive but not significant regression coefficient on short-term leverage and total leverage, while size has a negative but not significant regression coefficient on long-term leverage. However, size has a negative significant regression coefficient on market leverage. This suggests that high size firms are less likely to use market leverage for financing their investments than low size firms. Risk has a positive significant regression coefficient on short-term leverage and total leverage. This suggests that highly risk firms are more likely to use short-term leverage and total leverage for financing their investments than the low risk firms. Meanwhile, risk has a negative significant regression coefficient on long-term leverage this suggests that highly risk firms are less likely to use long-term leverage for financing their investments than the low risk firms. However, risk has a positive but not significant regression coefficient on market leverage. Growth has a positive significant regression coefficient on short-term, long-term, and total leverage, which suggests that highly growth firms are more likely to use short-term, longterm, and total leverage for financing their investments than the low growth firms. However, growth has a negative significant regression coefficient on market leverage. This suggests that high growth firms are less likely to use market leverage for financing their investments than the low growth firms. For hypothesis 2, from tables, we can conclude that the financing deficit has positive significant effects on net debt issue and on net equity issue. This result suggests that high deficit firms would tend to issue more net debt and net equity to finance the financing deficit. The financing deficit has negative but not significant effects on newly retained earning. This result suggests that high deficit firms would not tend to use newly retained earning to finance the financing deficit. The financing deficit has negative but not significant effects on repurchase 170

171 equity. This result suggests that high deficit firms would not tend to repurchase equity to finance the financing deficit. From the descriptive table, we see that the amount of net debt issue is more than net equity issue and it is consistent with regression results. For the augmented model, our result shows a positive coefficient on the financial deficit and also on the squared deficit term. However, for the squared deficit term, the coefficient was not significant. It implies that firms are limited by their debt capacity constraints and they have to resort to issuing equity. A squared deficit coefficient that is not large in absolute value implies a less reliance on equity finance for values of the financing deficit. Therefore, we can conclude that our sample of firm prefers external to internal financing and debt to equity if external financing is used. However, firms are limited by their debt capacity constraints and they have to resort to issuing equity. For hypothesis 3, the results indicate that net debt has no positive significant impact on the stock price of from January to December. This indicates that net debt has no significant impact on the yearly stock price. Net equity has no negative significant impact on the stock price from January to December. The result indicates that net equity has no significant impact on the stock price. This result suggests that firms that issue more net equity would tend to have decreasing stock price, while issue more net debt, the firm would tend to have increasing stock price. Result also suggests that firms that repurchase equity would tend to have increasing stock price. For hypothesis 4, the growing firms, from tables we can conclude that the financing deficit has positive significant effects on net debt issue, financing deficit has positive significant effects on net equity issue, and financing deficit has negative significant effects on newly retained earning. For mature firms, from tables we can conclude that the financing deficit has positive significant effects on net debt issue and net equity issue, while financing deficit has negative insignificant effects on newly retained earning. From these results, we can conclude that our mature and the sample of growth firms prefer external to internal financing and debt to equity if external financing is used. Overall, we find that the pecking order theory describes the financing patterns of growth firms better than mature firms as mature firms are more closely adopted by analysts and are better known to investors, and hence, should suffer less from problems of information asymmetry. 7.2 Conclusion regarding Result and Its Consistency with Condition of Indonesian Capital Market Our findings are implied that high growth firms in the manufacturing sector of the LQ45 Index are more likely to use short-term leverage, long-term leverage, and total leverage for financing their investments than low growth firms. However, firms with relatively high growth use less market leverage. Firms with relatively high growth will tend to issue securities less subject to information asymmetries, i.e. shot-term debt. Firms in the manufacturing sector of the LQ45 Index with relatively high growth are also to use more long-term and total leverage as when they use longterm leverage and total leverage for financing their investments, they have asset tangibility to secure their long-term debt. Even though high growth firms will face more information asymmetries, in the Indonesia Capital Market has already had the regulation to minimise information asymmetries, such as Regulation of Bapepam-LK No.X.K.1 regarding disclosure of information that must be announced to the public, and the attachment of Chairman Decision of Bapepam No.Kep-86/PM/1996 dated 24 January 1996 and Decision of the Board of Directors of PT. Indonesia Stock Exchange No: Kep- 171

172 306/BEJ/ dated July 19, 2004 concerning Rule Number I-E on the Obligation to Deliver Information. For firms in the manufacturing sector of the LQ45 Index, financing constraints will be more easily solved, as they have more access to banking. Banks will be more recognised and trusted than the companies. It is not excessive considering each moment banks can determine the condition of the company's financial through various disclosure of information which announced by the company in the Stock exchange. The rate of interest charged may also be lower, considering that the credit risk of public companies is relatively smaller. Generally the buyer of a letter of debt would certainly prefer if the company which issues letters of debt has become a public company, especially firms from the LQ45 Index. High profitability firms in the manufacturing sector of the LQ45 Index are less likely to use short-term leverage, long-term leverage, total leverage, and market leverage for financing their investments. Profitability firms in the manufacturing sector has low risk, firms prefer use more internal funds to external funds. High profitability firms in the manufacturing sector of the LQ45 Index use their retained earning and do not want to take benefit from the tax shield. Result showed that high risk firms in the manufacturing sector of the LQ45 Index have lower long-term leverage as long-term leverage need more collateral to secure this leverage. Earning volatility is proxy for the probability of financial distress and the firm will have to pay risk premium to outside fund providers. To reduce the cost of capital, a firm will first use internally generated funds and then outsider funds. However, our results showed that high risk firms in the manufacturing sector use more short-term leverage, total leverage, and market leverage than low risk firms. In Indonesia, for firms in the manufacturing sector of the LQ45 Index, financing constraints will be more easily solved, and rate of interest charged may also be lower, considering that the credit risk of public companies is relatively smaller, and generally the buyer of a letter of debt would certainly prefer if the company is from the LQ45 Index. Small firms often suffer the problems associated with asymmetric information, such as adverse selection, and they have to face higher bankruptcy costs, greater agency costs and bigger costs to resolve the higher informational asymmetries. That is why there is a positive relationship between size and STL and TLV of our manufacturing firm. As Rajan and Zingales (1995) argued that there was less asymmetrical information about the larger firms. This reduced the chances of undervaluation of the new equity issue and thus encouraged the large firms to use equity financing. Hence, larger firms in the manufacturing sector of the LQ45 Index have less long-term leverage and market leverage. Meanwhile, size positively related with total leverage and short-term leverage was consistent with trade-off theory. It implies that larger firms would take the tax shield benefit. Our results show that high tangibility firms in the manufacturing sector of the LQ45 Index use more long-term leverage, total leverage, and market leverage. Having the incentive of getting debt at lower interest rate, a firm with higher percentage of fixed asset is expected to borrow more as compared to a firm whose cost of borrowing is higher because of having less fixed assets. However, high tangibility firms in the manufacturing sector of the LQ45 Index use less short-term leverage, it implies that short-term leverage needs less tangibility of assets. For hypothesis 2, we imply that manufacturing firms of the LQ45 Index prefers external to internal financing and debt to equity if external financing is used. It follows pecking order theory. 172

173 In Indonesia, all listed firms, including older-mature-large and young-growth-small firms have less problems of information asymmetry as the government of Indonesia has issued the regulations in order to make all listed firms announce all information about firms. Firms in the manufacturing sector of the LQ45 Index firms have a good reputation to mitigate the adverse selection problem between borrowers and lenders. In Indonesia, by listing on the Indonesia Stock Exchange (IDX), banks can determine the condition of the company's financials through various disclosure of information which announced by the company in the Stock exchange. Rate of interest charged may also be lower considering that the credit risk of public companies is relatively smaller. The company in Indonesia has a variety of alternative to choose sources of funding, whether from inside or outside the company. Alternative funding from company is generally using retained earnings of the company. While alternative financing from external company comes from creditors in the form of debt, other forms of financing or the issuance of debentures, as well as equity in the form of shares. In Indonesia, the stock is one of the most popular financial market instruments. Issuing of shares is one of option to the company when they want to raise the fund. On the other hand, the stock is an investment instrument that has been chosen by the investor, because shares are able to provide an attractive rate of return. Stock can be defined as a sign of ownership of a person or party (entity) within a company. With the stock,that party has a claim on corporate earnings, claims on corporate assets, and the right to attend the general meeting of shareholders. The Indonesian capital market issued various regulations. However, all provisions will help companies to develop in a good way in the future. By issuing equity, many benefits can be obtained by the company including: obtaining new funding sources, providing competitive advantage for business development, merger or acquisition another company through the issuance of new shares, and increased the corporate value. For hypothesis 3, the results indicate that net debt has no positive significant impact on the stock price of from January to December. This indicates that net debt has no significant impact on the yearly stock price. Net equity has no negative significant impact on the stock price from January to December. The result indicates that net equity has no significant impact on the stock price. This result suggests that firms that issue more net equity would tend to have decreasing stock price, while issue more net debt, the firm would tend to have increasing stock price. Result also suggests that firms that repurchase equity would tend to have increasing stock price. In Indonesia, why can the stock price go up and down? Stock price movements are determined by supply and demand for these shares. Demand increases, the stock price increases and vice versa. Factors that affect stock price movements are including the movements in interest rates, inflation, exchange rate of the Rupiah, performance of the company, such as sales and profit increases, for dividends. For hypothesis 4, we imply that our growth and mature firms in the manufacturing sector of the LQ45 Index prefers external to internal financing and debt to equity if external financing is used. Therefore, both kinds of firms are following the pecking order theory. Specifically, the results imply that deficit of mature firms is solved more by net equity issue while deficit of growth firms is solved more by net debt issue. Following pecking order theory, growth firms should face more asymmetric information in capital markets. However, in the Indonesian capital market, namely IDX, information 173

174 asymmetry both for growth and mature firms has rarely happened as the government of Indonesia has stipulated the regulations regarding information asymmetry. The efforts of the government are as follow: doing Rationalisation for Information Disclosure Obligations of Issuer, develop Protection Scheme of Investor, and improving the Quality of Financial Transparency Information of Capital Market Industry To What Extent is the Study Scientifically Relevance The pecking order theory of capital structure is one of the most influential theories of corporate leverage. Firms seeking outside finance naturally face an adverse selection, and hence mispricing, problem. In order to avoid mispricing, firms finance investments internally if they can, and if they cannot, they prefer debt to equity since debt is less sensitive to outside investors not knowing the value of firms investment projects (Myers and Majluf, 1984). Shyam-Sunder and Myers (1999) show that the pecking order is a good first order description for the time series of debt finance for large mature firms. But these firms should face little asymmetric information in capital markets. Frank and Goyal (2003) argue that the support for the standard pecking order in Shyam- Sunder and Myers depends critically on their sample selection. Frank and Goyal argue that the sample selection of Shyam-Sunder and Myers picks large mature firms and that the standard pecking order is not a good description of the capital structure decisions for small, young firms in their larger sample. The results of Frank and Goyal (2003) study, conclude that the pecking order theory did not explain broad patterns in the data, and they argue that the sample selection of Shyam-Sunder and Myers picks large mature firms and that the standard pecking order is not a good description of the capital structure decisions for small, young firms in their larger sample. The Halov and Heider (2003) argument is that there is no reason to expect the standard pecking order to work well for all firms. However, our result summarised that the pecking order was a good descriptor of corporate financing behaviour for sample of corporations. Our result shows that firms prefer external to internal financing. Result also seems to suggest that firms rely more heavily on debt financing rather than on equity financing and it follow pecking order theory. Regarding the context of a firm s life cycle, our results also show that mature and growth firms are following the pecking order theory, even though 38.5% of our sample are mature firms. The evidence seems to suggest that mature and growth firms rely more heavily on external financing to internal financing and debt to equity if external financing is used, therefore they follow the pecking order theory. Our results also imply that the deficit of mature firms is solved more by net equity issue while deficit of growth firms is solved more by net debt issue. The pecking order theory predicts that firms with the greatest information asymmetry problems (specifically young, growth firms) are precisely those that should be making financing choices. Therefore, the pecking order theory describes the financing patterns of growth firms better than mature firms as our finding. On the subject of the determinants of capital structure of firms in the manufacturing sector in the Indonesian capital market, the effect of growth on leverage, our results showed that growth was positively related with short-term leverage, long-term leverage, and total leverage. It was consistent with the pecking order theory. Our results were in line with what agency costs/trade-off theory that the growth was negatively related with market leverage. For the effect of profitability on leverage, comparing the results with the theory, all of our results are negative and they are in line with the pecking order theory but contradicting with the trade-off theory. For 174

175 the influence of risk on leverage, our results showed that risk was negatively related with longterm leverage and it was in line with pecking order theory and trade-off theory. For the influence of size on leverage, our results showed a positive relation between size and short-term leverage and total leverage while our results that the size was negatively related with market leverage and long-term leverage were consistent with the pecking order theory. According to the pecking order theory, there will be a negative relationship between leverage and firm size. For the impact of tangibility on leverage, if we compare the results to the theory, the tangibility is negatively related with short-term leverage, and it is not in line with the pecking order theory and trade-off theory. For the relationship between tangibility and long-term leverage, total leverage, and market leverage, are in line with the pecking order theory (positive) and tradeoff theory (positive). Concerning the effect of issuing debt on stock price, there were several theories that explained the relationship between capital structure and stock price, such as signalling through capital structure, pecking order theory, and trade-off theory. Our result is positive. This is consistent with signalling through capital structure that the increased level of debt indicates the confidence of the management in the future. Hence it carries greater conviction than a mere announcement of undervaluation of the firm by the management. The markets normally react favourably to moderate increases in leverage and negatively to fresh issue of equity. Our result is also consistent with the pecking order theory, as securities with less adverse selection (debt) will result in less negative or no market reaction. Finally, our result is in line with the trade-off theory. If the firm issued securities to take advantage of a promising new opportunity, so it would be good news to the market. Regarding the influence of issuing equity on stock price, when we compared the results to the theory of predictions, our results were consistent with the theory of signalling through capital structure, pecking order theory, and Jung et al. (1996). Jung et al. (1996) suggested an agency perspective and argued that equity issues by firms with poor growth prospects reflected agency problems between managers and shareholders where stock prices would react negatively to news of equity issues. Regarding repurchased the stock on stock price. Literature offers multiple explanations for buybacks. One of these explanations is the information/signalling hypothesis. Because of the asymmetric information between managers and shareholders, share repurchase announcements are considered to reveal private information that managers have about the value of the company. According to the information/signalling hypothesis, repurchase announcements should be accompanied by positive price changes. Hence, overall, our result is in line with the information/ signalling hypothesis that has immediate implications: repurchase announcements should be accompanied by positive price changes. From our analysis above, most of our result is consistent with the theories prediction. Therefore, our study is scientifically still relevant Recommendations and Suggestions for Further Research Based on the findings and limitations of the research, the following recommendations can be made for further research: 1. As we have got low R-squared and adjusted R-squared, it is recommended to extend longer sampling period and to add the number of sample firms, so that we can reach higher R-squared and adjusted R-squared. 175

176 2. In result of hypotheses testing 2 and 3, scatterplot and normal p-p plot indicate that dots are rarely distributed as data we used are limited. Hence, longer sampling period and larger amount of sample firms are recommended to use in further research. 3. In further research, the other indices are recommended to use as sample, so that we can compare our result with another result. 4. As the purpose of our research will not be to produce a theory that is generalisable to all populations, but will be simply to try to explain what is happening with our research setting, the Indonesian capital market, therefore, it may be suggested to other researchers to test the other research settings in a follow-up study Suggestions for Managers As the result indicates that net debt issue has positive impact on the stock price of from January to December, and on the yearly stock price, it is a good choice if firms issue more debt and inform the market. So stock price will increase. On the other hand, the net equity issue has negative effect on the stock price from January to December. It is suggested to firms to issue less net equity to anticipate the fall of stock price. Result also suggests that firms can repurchase equity and announce to public, and will follow by getting higher stock price Managerial Implication The issue of capital structure is an important strategic financing decision that firms have to make. Therefore, the results of this study provide some useful information about the capital structures of firms in the manufacturing sector of the LQ45 Index in Indonesia. As a conclusion, it can be stated that the findings show evidence that the pecking order theory and trade-off theory appear to dominate the firms capital structure in Indonesia. From the results, we can recognise exactly to what extent the firms in manufacturing sector in Indonesia choose or mix capital structure, based on the following results: - Determinants or firms characteristics in the manufacturing sector in Indonesia. - How firms in the manufacturing sector in Indonesia finance their deficit. - The impact of choosing capital structure on the firm s stock price. - What is the choice of capital structure over the firms life cycle in the manufacturing sector in Indonesia to finance the investments. So that the firms can make the financial policy to what extent they choose or mix capital structure based on the following consideration: - Determinant or firms characteristics - Hierarchy preference and cost and benefit which need to trade-off - The impact on firm stock price - Firms life cycle 176

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186 APPENDIX APPENDIX A Regression Results Regression Results of Hypothesis 1 Correlation Test Results Pearson Correlation Pearson Correlation Pearson Correlation Pearson Correlation Sig. (1- tailed) STL PRFT TANG SIZE RISK GROW STL PRFT TANG SIZE RISK.222 LTL PRFT TANG SIZE RISK GROW LTL TL PRFT TANG SIZE RISK GROW TLV MRL PRFT TANG SIZE RISK GROW MRL STL PRFT TANG SIZE RISK..001 LTL TLV MRL Descriptive Statistics Descriptive Statistics Mean Std. Deviation STL LTL TLV MRL PRFT TANG SIZE RISK

187 GROW Anova Test Results ANOVA Model Sum of df Mean F Sig. Squares Square STL Regression a Residual Total LTL Regression a Residual Total TLV Regression a Residual Total MRL Regression a Residual Total a. Predictors: (Constant), GROW, TANG, RISK, SIZE, PRFT Anova Test Results Model R Square Adjusted R Square ANOVA-F Sig. Durbin- Watson STL a LTL a TLV a.994 MRL a a. Predictors: (Constant), Growth, Tangibility, Risk, Size, Profitability Model Summary Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate STL.576 a LTL.537 a TLV.809 a MRL.799 a a. Predictors: (Constant), GROW, TANG, RISK, SIZE, PRFT Durbin- Watson 187

188 Result of Regression of Hypothesis 2 Issue Debt and Issue Equity Descriptive Statistics Descriptive Statistics Mean Std. Deviation NDEBT FD NEQUITY FD NRE FD NDEBT FD FDSQR Correlations Test Results Correlations NDEBT FD Pearson NDEBT Correlation FD Sig. (1-tailed) NDEBT..000 FD.000. NEQUITY FD Pearson NEQUITY Correlation FD Sig. (1-tailed) NEQUITY..000 FD.000. NRE FD Pearson NRE Correlation FD Sig. (1-tailed) NRE..044 FD.044. Augmented Test Results Correlations Pearson Correlation NDEBT FD FDSQR NDEBT FD FDSQR Sig. (1-tailed) NDEBT FD FDSQR

189 Model Summary Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate NDEBT.775 a NEQUITY.464 a NRE.236 a NDEBT.777 a a. Predictors: (Constant), FDSQR, FD Durbin- Watson Anova Test Results ANOVA b Model Sum of df Mean F Sig. Squares Square NDEBT Regression a Residual NEQUIT Y Total Regression a Residual Total NRE Regression a Residual Total NDEBT Regression a Residual Total a. Predictors: (Constant), FDSQR, FD b. Dependent Variable: NDEBT Issue Debt to Repurchase Equity Descriptive Statistics Descriptive Statistics Mean Std. Deviation ISSUEDEBT FD REPOEQUITY FD NRE FD

190 Correlations Test Results Correlations ISSUEDEBT FD Pearson ISSUEDEBT Correlation FD Sig. (1-tailed) ISSUEDEBT..004 FD.004. REPOEQUITY FD Pearson REPOEQUITY Correlation FD Sig. (1-tailed) REPOEQUITY..497 FD.497. NRE FD Pearson NRE Correlation FD Sig. (1-tailed) NRE..000 FD.000. Model Summary Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate ISSUEDEBT.508 a REPOEQUITY.002 a NRE.691 a a. Predictors: (Constant), FD b. Dependent Variable: NRE Durbin- Watson Anova Test Results ANOVA b Model Sum of df Mean F Sig. Squares Square ISSUEDEBT Regression a Residual Total REPOEQUITY Regression a Residual Total NRE Regression a Residual Total a. Predictors: (Constant), FD b. Dependent Variable: NRE 190

191 Collinearity Diagnostics Collinearity Diagnostics a Model Dimension Eigen value Condition Index Variance Proportions (Constant) FD ISSUEDEBT REPOEQUITY NRE a. Dependent Variable: NRE Regression Results of Hypothesis 3 H3a-NDEBT Descriptive Statistics Descriptive Statistics Mean Std. Deviation Jan NDebt Feb NDebt Mar NDebt Apr NDebt May NDEBT Jun NDebt Jul NDebt Aug NDebt Sep NDebt Oct NDebt Nov NDebt Dec NDebt P_yearly NDebt

192 Correlations Test Results Correlations Jan NDEBT Pearson Correlation Jan NDEBT Sig. (1-tailed) Jan..039 NDEBT.039. Feb NDEBT Pearson Correlation Feb NDEBT Sig. (1-tailed) Feb..044 NDEBT.044. Mar NDEBT Pearson Correlation Mar NDEBT Sig. (1-tailed) Mar..042 NDEBT.042. Apr NDEBT Pearson Correlation Apr NDEBT Sig. (1-tailed) Apr..049 NDEBT.049. May NDEBT Pearson Correlation may NDEBT Sig. (1-tailed) May..044 NDEBT.044. Jun NDEBT Pearson Correlation Jun NDEBT Sig. (1-tailed) Jun..043 NDEBT.043. Jul NDEBT Pearson Correlation Jul NDEBT Sig. (1-tailed) Jul..051 NDEBT.051. Aug NDEBT Pearson Correlation Aug NDEBT Sig. (1-tailed) Aug..052 NDEBT.052. Sep NDEBT Pearson Correlation Sep NDEBT Sig. (1-tailed) Sep..058 NDEBT

193 Correlations Test Results Correlations Oct NDEBT Pearson Correlation Oct NDEBT Sig. (1-tailed) Oct..056 NDEBT.056. Nov NDEBT Pearson Correlation Nov NDEBT Sig. (1-tailed) Nov..058 NDEBT.058. Dec NDEBT Pearson Correlation Dec NDEBT Sig. (1-tailed) Dec..057 NDEBT.057. Correlations Test Results - P_yearly Correlations P_yearly NDEBT Pearson P_yearly Correlation NDEBT Sig. (1-tailed) P_yearly..351 NDEBT.351. P_yearly NDEBT Model Summary Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Jan.189 a Feb.183 a Mar.185 a Apr.176 a May.181 a Jun.182 a Jul.172 a Aug.171 a Sep.164 a Oct.164 a Nov.161 a Dec.159 a Durbin- Watson

194 Yearly.027 a a. Predictors: (Constant), NDEBT b. Dependent Variable: P_yearly Anova Test Results Model Sum of df Mean F Sig. Squares Square Regression 5.741E E a Jan Residual 1.542E E7 Total 1.600E9 87 Regression 5.223E E a Feb Residual 1.506E E7 Total 1.559E9 87 Regression 4.723E E a Mar Residual 1.328E E7 Total 1.375E9 87 Regression 3.966E E a Apr Residual 1.247E E7 Total 1.287E9 89 Regression 4.258E E a May Residual 1.263E E7 Total 1.306E9 89 Regression 4.163E E a Jun Residual 1.218E E7 Total 1.260E9 89 Regression 4.369E E a Jul Residual 1.426E E7 Total 1.469E9 90 Regression 3.758E E a Aug Residual 1.245E E7 Total 1.282E9 90 Regression 3.451E E a Sep Residual 1.243E E7 Total 1.277E9 92 Regression 3.802E E a Oct Residual 1.375E E7 Total 1.413E9 94 Regression 3.900E E a Nov Residual 1.467E E7 Total 1.506E9 96 Regression 4.255E E a Dec Residual 1.649E E7 Total 1.691E9 100 Regression 1.219E E a Yearly Residual 1.614E E7 Total 1.616E a. Predictors: (Constant), NDEBT 194

195 b. Dependent Variable: P_yearly H3b-NEQUITY Descriptive Statistics Descriptive Statistics Mean Std. Deviation Jan NEQUITY Feb NEQUITY Mar NEQUITY Apr NEQUITY May NEQUITY Jun NEQUITY Jul NEQUITY Aug NEQUITY Sep NEQUITY Oct NEQUITY Nov NEQUITY Dec NEQUITY P_yearly NEQUITY Correlations Test Results Correlations Jan NEQUIT Y Pearson Correlation Jan NEQUIT Y Sig. (1-tailed) Jan..266 NEQUIT.266. Y Feb NEQUITY 195

196 Pearson Correlation Feb NEQUIT Y Sig. (1-tailed) Feb..269 NEQUIT.269. Y Mar NEQUITY Pearson Correlation Mar NEQUIT Y Sig. (1-tailed) Mar..268 NEQUIT.268. Y Apr NEQUITY Pearson Correlation Apr NEQUIT Y Sig. (1-tailed) Apr..265 NEQUIT.265. Y May NEQUITY Pearson Correlation May NEQUIT Y Sig. (1-tailed) May..267 NEQUIT.267. Y Jun NEQUITY Pearson Correlation Jun NEQUIT Y Sig. (1-tailed) Jun..265 NEQUIT.265. Y Jul NEQUITY Pearson Correlation Jul NEQUIT Y Sig. (1-tailed) Jul..227 NEQUIT.227. Y Aug NEQUITY Pearson Correlation Aug NEQUIT Y Sig. (1-tailed) Aug..230 NEQUIT.230. Y Sep NEQUITY 196

197 Pearson Correlation Sep NEQUIT Y Sig. (1-tailed) Sep..217 NEQUIT Y.217. Correlations Test Results Correlations Oct NEQUITY Pearson Correlation Oct NEQUIT Y Sig. (1-tailed) Oct..232 NEQUIT.232. Y Nov NEQUITY Pearson Correlation Nov NEQUIT Y Sig. (1-tailed) Nov..238 NEQUIT.238. Y Dec NEQUITY Pearson Correlation Dec NEQUIT Y Sig. (1-tailed) Dec..261 NEQUIT.261. Y P_yearly NEQUITY Pearson Correlation P_yearly NEQUIT Y Sig. (1-tailed) P_yearly..176 NEQUIT Y.176. Model Summary Model Summary b Model R R Adjusted R Std. Error of the Square Square Estimate Jan.067 a Feb.066 a Mar.067 a Apr.067 a Durbin- Watson

198 May.066 a Jun.067 a Jul.080 a Aug.079 a Sep.082 a Oct.076 a Nov.073 a Dec.064 a yearly.067 a a. Predictors: (Constant), NEQUITY b. Dependent Variable: P_yearly Anova Test Results ANOVA b Model Sum of df Mean Square F Sig. Squares Regression a Jan Residual 1.592E E7 Total 1.600E9 87 Regression a Feb Residual 1.552E E7 Total 1.559E9 87 Regression a Mar Residual 1.369E E7 Total 1.375E9 87 Regression a Apr Residual 1.281E E7 Total 1.287E9 89 Regression a May Residual 1.300E E7 Total 1.306E9 89 Regression a Jun Residual 1.254E E7 Total 1.260E9 89 Regression a Jul Residual 1.460E E7 Total 1.469E9 90 Regression a Aug Residual 1.274E E7 Total 1.282E9 90 Regression a Sep Residual 1.269E E7 Total 1.277E9 92 Regression a Oct Residual 1.405E E7 Total 1.413E9 94 Regression a 198

199 Nov Residual 1.498E E7 Total 1.506E9 96 Regression a Dec Residual 1.684E E7 Total 1.691E9 100 Regression 7.226E E a Yearly Residual 1.608E E7 Total 1.616E a. Predictors: (Constant), NEQUITY b. Dependent Variable: P_yearly H3c-Issue Debt to Repurchase Equity Descriptive Statistics Descriptive Statistics Mean Std. Deviation Jan E3 NDEBT NEQUITY Feb E3 NDEBT NEQUITY Mar E3 NDEBT NEQUITY Apr E3 NDEBT NEQUITY May E3 NDEBT NEQUITY Jun E3 NDEBT NEQUITY Jul E3 NDEBT NEQUITY Aug E3 NDEBT NEQUITY Sep E3 NDEBT NEQUITY Oct E3 NDEBT NEQUITY Nov E3 199

200 NDEBT NEQUITY Dec E3 NDEBT NEQUITY P_yearly E3 NDEBT NEQUITY Correlations Test Results Correlations Pearson Correlation Jan NDEBT NEQUITY Jan NDEBT NEQUITY Sig. (1-tailed) Jan NDEBT NEQUITY Feb NDEBT NEQUITY Pearson Correlation Feb NDEBT NEQUITY Sig. (1-tailed) Feb NDEBT NEQUITY Mar NDEBT NEQUITY Pearson Correlation Mar NDEBT NEQUITY Sig. (1-tailed) Mar NDEBT NEQUITY Apr NDEBT NEQUITY Pearson Correlation Apr NDEBT NEQUITY Sig. (1-tailed) Apr NDEBT NEQUITY May NDEBT NEQUITY Pearson Correlation May NDEBT NEQUITY Sig. (1-tailed) May NDEBT NEQUITY Jun NDEBT NEQUITY 200

201 Pearson Correlation Jun NDEBT NEQUITY Sig. (1-tailed) Jun NDEBT NEQUITY Correlations Test Results Pearson Correlation Jul NDEBT NEQUIT Y Jul NDEBT NEQUITY Sig. (1-tailed) Jul NDEBT NEQUITY Aug NDEBT NEQUITY Pearson Correlation Aug NDEBT NEQUITY Sig. (1-tailed) Aug NDEBT NEQUITY Sep NDEBT NEQUITY Pearson Correlation Sep NDEBT NEQUITY Sig. (1-tailed) Sep NDEBT NEQUITY Oct NDEBT NEQUITY Pearson Correlation Oct NDEBT NEQUITY Sig. (1-tailed) Oct NDEBT NEQUITY Nov NDEBT NEQUITY Pearson Correlation Nov NDEBT NEQUITY Sig. (1-tailed) Nov NDEBT NEQUITY Dec NDEBT NEQUITY Pearson Correlation Dec NDEBT

202 NEQUITY Sig. (1-tailed) Dec NDEBT NEQUITY P_yearly NDEBT NEQUITY Pearson Correlation P_yearly NDEBT NEQUITY Sig. (1-tailed) P_yearly NDEBT NEQUITY Anova Test Results ANOVA b Model Sum of df Mean Square F Sig. Squares Jan Regression 1.120E E a Residual 5.627E E7 Total 6.748E8 8 Feb Regression 1.111E E a Residual 5.733E E7 Total 6.844E8 8 Mar Regression 1.076E E a Residual 4.406E E7 Total 5.482E8 8 Apr Regression 1.013E E a Residual 3.420E E7 Total 4.434E8 8 May Regression 8.636E E a Residual 3.558E E7 Total 4.422E8 8 Jun Regression 7.276E E a Residual 3.112E E7 Total 3.840E8 8 Jul Regression 8.005E E a Residual 4.085E E7 Total 4.885E8 8 Aug Regression 7.434E E a Residual 3.520E E7 Total 4.263E8 8 Sep Regression 7.588E E a Residual 2.762E E7 Total 3.520E

203 Anova Test Results ANOVA b Oct Regression 6.774E E a Residual 1.760E E7 Total 2.437E8 8 Nov Regression 8.782E E a Residual 2.206E E7 Total 3.084E8 8 Dec Regression 1.020E E a Residual 2.226E E7 Total 3.246E8 9 yearly Regression 9.586E E a Residual 6.428E E7 Total 7.387E8 22 a. Predictors: (Constant), NEQUITY, NDEBT b. Dependent Variable: P_yearly Model Summary Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Jan.407 a E3.987 Feb.403 a E Mar.443 a E3.890 Apr.478 a E3.684 May.442 a E3.813 Jun.435 a E3.762 Jul.405 a E3.868 Aug.418 a E3.754 Sep.464 a E3.598 Oct.527 a E3.806 Nov.534 a E3.800 Dec.561 a E3.888 yearly.360 a E a. Predictors: (Constant), REPOEQUITY, NDEBT b. Dependent Variable: P_yearly Durbin- Watson Regression Results of Hypothesis 4 Growth and Mature Firms Descriptive Statistics Sum Mean Sum Mean LTL_G LTL_M FIXAS_G FIXAS_M

204 DIV_G DIV_M dwc_g dwc_m CF_G CF_M FD_G FD_M FDSQR_G FDSQR_M NRE_G NRE_M NEQUITY_G NEQUITY_M NDEBT_G NDEBT_M Valid N Valid N (listwise) (listwise) Descriptive Statistics Test Results Mean Std. Deviation NDEBT_M FD_M NEQUITY_M FD_M NDEBT_G FD_G NEQUITY_G FD_G Correlations Test Results NDEBT_M FD_M Pearson NDEBT_M Correlation FD_M Sig. (1-tailed) NDEBT_M FD_M NEQUITY_M FD_M Pearson NEQUITY_M Correlation FD_M Sig. (1-tailed) NEQUITY_M FD_M NDEBT_G FD_G Pearson NDEBT_G Correlation FD_G Sig. (1-tailed) NDEBT_G FD_G NEQUITY_G FD_G Pearson NEQUITY_G Correlation FD_G Sig. (1-tailed) NEQUITY_G FD_G

205 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Durbin- Watson NDEBT_M a NEQUITY_M a NDEBT_G a NEQUITY_G a a. Predictors: (Constant), FD_G Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Durbin- Watson NDEBT_M a NDEBT_G a a. Predictors: (Constant), FDSQR_G, FD_G and M b. Dependent Variable: NDEBT_G and M Anova Test Results Model Sum of df Mean F Sig. Squares Square NDEBT_M Regression a Residual Total NEQUITY_M Regression a Residual Total NDEBT_G Regression a Residual Total NEQUITY_G Regression a Residual Total a. Predictors: (Constant), FD_G 205

206 APPENDIX B List of Acronyms Table B.1. Name of Firms Name of Firms ASII AUTO ADMG BRPT BUDI CPIN DNKS FASW GGRM GJTL HMSP INAF INDF INDR INKP INTP KAEF KLBF KOMI RMBA SMCB SMGR TKIM TSPC UNVR SULI Acronyms Astra International Astra Otoparts Polychem Indonesia Barito Pacific Budi Acid Jaya Charoen Pokphand Indonesia Dankos Laboratories Fajar Surya Wisesa Gudang Garam Gajah Tunggal Hanjaya Mandala Sampoerna Indofarma Indocement Tunggal Prakasa Indorama Synthetics Indah Kiat Pulp and Paper Indocement Tunggal Prakasa Kimia Farma Kalbe Farma Komatsu Indonesia Bentoel International Investama Holcim Indonesia Semen Gresik (Persero) Pabrik Kertas Tjiwi Kimia Tempo Scan Pacific Unilever Indonesia Sumalindo Lestari Jaya Table B.2. Variables and Its Sub-variables of Research Variables of Research Aug Apr CAPEX CF CF_M CF_G Acronyms August stock price April stock price Capital expenditures Operating cash flow (after interest and taxes) Cash flow of mature firm Cash flow of growth firm 206

207 DIV DIV_G DIV_M DC Dec dwc_g dwc_m dworking capital dta dre deq Fixed Assets Working Capital Long Term Debt ΔTD Feb FD FDSQR FD_G FDSQR_G FD_M FDSQR_M FD_L FDSQR_L FD_S FDSQR_S FD_O FDSQR_O FD_Y Dividend payments Dividend payments of growth firm Dividend payments of mature firm Domestic corporation December stock price Change in working capital of growth firm Change in working capital of mature firm The net change in working capital Change in total asset Change in retained earning Change in book equity Change in fixed assets Change in working capital Change in long term debt Change in total debt (long term plus short term) February stock price Financing deficit Financing deficit square Financing deficit of growth firm Financing deficit square of growth firm Financing deficit of mature firm Financing deficit square of mature firm Financing deficit of large firm Financing deficit square of large firm Financing deficit of small firm Financing deficit square of small firm Financing deficit of old firm Financing deficit square of old firm Financing deficit of young firm 207

208 FDSQR_Y FIXAS_G FIXAS_M GCC countries Growth GROW Jan JM Jun Jul LTL_M LTL_G LTD payment Large LTL May MRL MM MNC Mature Mar MV of equity NDEBT_G NEQUITY_G NDEBT_M NEQUITY_M Financing deficit square of young firm Fixed asset of growth firm Fixed asset of mature firm Gulf Cooperation Council (GCC) countries Growth firm Growth January stock price Jensen and Meckling June stock price July stock price Long-term leverage of mature firm Long-term leverage of growth firm Long-term debt payment Large firm Long-term leverage May stock price Market leverage The Modigliani-Miller Multi National Corporation Mature firm March stock price Market value of equity Net debt issue of growth firm Net equity issue of growth firm Net debt issue of mature firm Net equity issue of mature firm 208

209 NRE_G NRE_M NDEBT_L NEQUITY_L NRE_L NDEBT_S NEQUITY_S NRE_S NDEBT_O NEQUITY_O NRE_O NDEBT_Y NEQUITY_Y NRE_Y Net debt it Net debt t NPV Nov NDEBT NEQUITY NRE Oct Old P_Yearly PRFT POT Newly retained earning of growth firm Newly retained earning of mature firm Net debt issue of large firm Net equity issue of large firm Newly retained earning of large firm Net debt issue of small firm Net equity issue of small firm Newly retained earning of small firm Net debt issue of old firm Net equity issue of old firm Newly retained earning of old firm Net debt issue of young firm Net equity issue of young firm Newly retained earning of young firm Net debt issued in period t scaled by total assets at the beginning of period t (asset t-1 ) Long-term debt issuance at t minus long-term debt reduction at t divided by total assets at t-1. Net present value November stock price Net debt issue Net equity issue Newly retained earning October stock price Old firm Yearly stock price Profitability Pecking order theory 209

210 REPO EQUITY_G REPO EQUITY_L REPO EQUITY_S REPO EQUITY_Y REPO EQUITY_O REPO EQUITY_M RISK ROA REPO EQUITY Sep SIZE STL Small TANG Tobin s Q TE TLV Young Repurchase equity of growth firm Repurchase equity of large firm Repurchase equity of small firm Repurchase equity of young firm Repurchase equity of old firm Repurchase equity of mature firm Risk Return on Asset Repurchase equity September stock price Firm s size Short-term leverage Small firm Asset tangibility Proxy of future growth opportunities Total equity Total leverage Young firm Table B.3. Variables of Capital Market Variables of Capital Market BAPEPAM Bapepam-LK BEI Acronyms Badan Pengawas Pasar Modal (Capital Market Supervisory Agency) Badan Pengawas Pasar Modal (Capital Market Supervisory Agency) Lembaga Keuangan Bursa Efek Indonesia BISNIS-27 Business 27 CPI CSPI DBX GDP Consumer Price Index Composite Stock Price Index Development Board Index Gross Domestic Product 210

211 ICT IDR IDX IPO JATS JSX Kompas 100 LQ45 Index MBX Information and communication technology Indonesian Rupiah Indonesia Stock Exchange Initial Public Offering Jakarta Automatic Trading System Jakarta Stock Exchange Index consists of 100 shares of Listed Companies that are selected based on considerations of liquidity and market capitalisation Liquid 45 Index Main Board Index MUI The Majelis Ulama Indonesia (the Sharia Supervisory Board) No.Kep-86/PM/1996 Nomor Keputusan-86/Pasar Modal/1996 PEFINDO-25 PT Pemeringkat Efek Indonesia 25 (rating agencies) Perusahaan terbatas KEHATI Sustainable Responsible Investment-Indonesian Biodiversity Foundation SME Small Medium Enterprises TBK The BNDES USD U.S. YOY Terbuka The state-owned development bank U.S. Dollar United States Year on year Table B.4. Variables in Statistics Statistics Adjusted R -squared ANOVA B Beta Acronyms Adjusted R Squared is designed to more closely reflect how well the model fits the population and is usually of interest for models with more than one predictor. Analysis of Variance Unstandardised Coefficients Standardised Coefficients Beta 211

212 DW F-statistic Durbin Watson Test of autocorrelation The t test results of two groups to three or more groups H1, H2, H3, and H4 Hypothesis 1, Hypothesis 2, Hypothesis 3, and Hypothesis 4 OLS regressions Ordinary least square regressions R -squared The Coefficient of Determination = its value is always between 0 and 1, and interpreted as the percentage of variation of the response variables explained by the regression line. R The multiple correlation coefficients are the linear correlation between the model-predicted and the observed values of the dependent variable. Normal P-P plot The histogram gave the normally pattern of distribution N QUAN QUAL Sig. SPSS Std. Deviation Std. Error of Skewness Number of observation Quantitative Qualitative Significance level Statistical Package for Social Science Standard deviation Standard error of skewness Std. Error of Kurtosis Std. Error T The p-value VIF Standard error of kurtosis Standard error of unstandardised coefficients t-value of regression Significance level Variance Inflation Factor 212

213 APPENDIX C List of Figures from Regression Results Figures of Hypothesis 1 Testing Result 213

214 Figures of Hypothesis 2 Testing Result 214

215 215

216 Figures of Hypothesis 3 Testing Result 216

217 217

218 Figures of Hypothesis 4Testing Result 218

219 219

220 APPENDIX D Results of Panel Data Regression Analysis Result of Hypothesis 1 220