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Evaluating Capital Structure Across Developed And Developing Countries

The following paper investigates how capital structure differs across countries, specifically the difference or lack thereof between leverage and capital structure determinants between developed and developing countries. A cross section of 1198 firms across 8 countries are investigated and I find that there are no significant differences to determinants of capital structure between countries that are considered developed and countries that are developing. In addition my research shows that the main variables which affect capital structure are tangibility of assets and profitability of a firm. The results of how firm size and investment opportunities proved to be inconclusive in how they affect leverage.

Introduction

Thesis Statement;

“There is no significant difference to the Determinants of Capital Structure of Developing Countries to those of Developed Countries”

Capital structure refers to the way a firm chooses to finance its assets and investments through some combination of equity, debt, or internal funds. It is in the best interests of a company to find the optimal ratio of debt to equity to reduce their risk of insolvency, continue to be successful and ultimately remain or to become profitable.

Capital structure is a crucial component in all parts of finance and has been debated for over 50 years since the seminal paper of Modigliani and Miller (1958) "The Cost of Capital, Corporate Finance, and the Theory of Investment". Since then a vast amount of papers and empirical research about the theories of capital structure for example the Pecking Order Theory and Trade-off Theory as well as literature relating to what are the true determinants of capital structure and how it is affected by industries or country specific reasons. This empirical research is another step in exploring capital structure and how the determinants differ across developing and developed world.

The main motivation for conducting my research on the topic of capital structure and specifically how it affects developing countries is twofold. Firstly I found the lecture topic I attended at Queens University given by Professor John Turner and Christopher Coyle to be of great interest to me and after reading the paper written by Rajan and Zingales (1995) I found the subject very intriguing and wanted to research it further. Secondly I found there was an array of conflicting results and conclusions in literature I read on how different countries legal systems affected capital structure. This motivated me to investigate if there were difference in the factors which affect leverage across countries.

This paper will therefore answer the following research questions;

Does firms leverage significantly differ across developing and developed countries?

Do the determinants of capital structure significantly differ across countries?

Do the determinants of capital structure significantly differ between developing and developed countries?

The data set used is of the year end 2010 and consists of data of the top 200 firms in terms of market capitalizing of 8 countries; 4 developed countries (USA, UK, Germany and Japan) and 4 developing countries (Brazil, Russia, India and China). The determinants of capital structure I have decided to use have come from Rajan and Zingales (1995). These are tangibility of assets, firm size, profitability and investment opportunities. Osiris Database was used to collect the data and the regression conducted on STATA econometrics software package.

This paper finds that although there are some differences between the aggregate levels of leverage in countries that overall there are no significant differences to the determinants of capital structure across developing and developed countries. Furthermore the findings show that profitability has a negative on capital structure in all 8 countries and tangibility of assets has a positive effect on leverage in developing and developed countries. The variables of size and investment opportunities of a firm differ across all countries but not specifically between developing and developed. These variables do not influence capital structure to the same degree as profitability or tangibility of assets.

The rest of the paper proceeds as follows: Section I reviews literature of related work on capital structure and the determinants of capital structure. Section II describes the data set I have collected and the methodology used to conduct my research. Section III presents empirical results of my findings and interpretation of my results. Section IV concludes and suggests areas for future research. Finally section V lists my references.

Section I. Literature Review

International studies of capital structure and its determinant dates back to the paper Modigliani and Miller (1958). They stated that in a simplified world that it did not matter whether a firm financed investments through debt or equity famously known as the Irrelevancy Theorem. Modigliani and Miller (1963) then went on to point out that if companies can deduct debt interest before arriving at taxable profits hence concluding that a firm should finance full with debt. Since then there have been vast amounts of empirical studies on this topic; expressing different and conflicting views as to what really determines optimal capital structure.

The most prominent paper in the literature of capital structure is Rajan and Zingales (1995) “What do we know about Capital structure? Some evidence from international data.” In this paper they investigated the determinants of capital structure choice of public firms in G7 countries. The authors look at the institutional differences across the seven countries and identify the main determinants of capital structure. One of their main findings was that firm leverage is reasonably similar across countries and considerably more similar than it had once been believed. Furthermore they did find that firms in the UK had lower level of debt than in the other six countries. They argue that although common firm-specific factors significantly influence the capital structure of firms across countries, several country-specific factors also play an important role. They concluded that tangibility of assets, firm size, profitability and growth of firm explain 19% of the cross-sectional differences in firms' leverage. At the same time, they find country-specific differences in capital structure choices due to the tax policies and agency problems, differences in bankruptcy laws and moral hazard costs across countries. Rajan and Zingales (1995) state “tangible assets are easy to collateralize and thus they reduce the agency costs of debt.” They also found that profitability was negatively correlated with firm leverage, i.e. the more profitable a firm was, the less leverage they would have. Although Rajan and Zingales study concludes there are both firm specific and country specific factor the purpose of this current research paper is to prove that the determinants of capital structure do not differ across developing and developed countries. As previously stated I will use the determinants Rajan and Zingales (1995) found significant in this research.

In terms of the tangibility of assets Jensen and Mekling (1976) along with Harris and Raviv, (1991) found that the relationship between lenders and firms is conflicted known as the Agency Cost Theory. Briefly the agency cost theory suggests there is an incentive for managers of companies to invest in a suboptimal way as they have more information about the firm than the lenders. This forces lenders to require tangible assets as security against default of debt repayments. This is very common in debt financing.

The Pecking Order Theory, based on work of Myers and Majluf (1984) suggests that firms have a pecking-order in the choice of financing their activities. Managers know more about the true value of the firm and the firm’s investment risk than outside investors. To avoid the underinvestment, managers will seek to finance the new project using funds that are not costly to the firm, such as it own internal profits. Thus, this affects the decision between internal and external financing. The pecking order theory explains why firms tend to depend on internal sources of funds and prefer debt to equity if external financing is required. This would mean that the more profitable an organisation is the less inclined it would be to take on debt.

Under the agency cost theory, Jensen and Meckling (1976), Myers (1977) and Jensen (1986) muse that firms debt financing to alleviate the conflict of interest between managers and shareholders with regards to excess profits in an organisation. Such agency cost being employee shirking, managers taking on excess risk as he will seek the rewards if it pays off and not feel any of the burdens if it doesn’t. These theories predict that firms maintain an optimum capital structure where the marginal benefit of debt equals the marginal cost.

Fama and Jensen (1983) believed there are more information available to investors about large firms, particularly those traded on an exchange which leads to less asymmetric information about large firms increasing their preference to finance through equity rather than debt thus concluding a negative relationship between firm size and debt. This corresponds to what (Rajan and Zingales, 1995) found.

As described before the pecking order theory would imply that companies will prefer to debt finance if external financing is needed to finance investment opportunities. In contrast it has been argued that high growth firms will face difficulties in borrowing as they may be relatively new and of greater risk than other industries causing the need from investors to require greater interest payments in return Myers (1977). For this reason, we may now instead expect a negative relationship between growth and capital structure.

Demirguc-Kunt and Maksimovic (1999) compare leverage of firms from 19 developed countries and 11 developing countries. They find that institutional factors between countries describe the differences in the capital structure, specifically the long-term debt to total assets. Developed countries firms have more long-term debt and a greater amount of their total debt is held as long-term debt and that large firms have more long-term debt as a proportion of total assets and debt. They believe that cross-country variations in leverage can be described by difference in the legal systems and financial institutions, as well as firm industry and macroeconomic factors, such as the rate of inflation and the economy’s growth rate.

Booth et al. (2001) examined the capital structures of firms across 10 developing countries finding that leverage determinants of firms in developing countries are affected by the same firm-specific factors as in developed countries. However, they find that there are differences in the way leverage is affected by country-specific factors such as development of stock and bond market and other economic factors. The most significant result they found was that the more profitable the firm was the lower the amount of leverage. This is consistent with the pecking order theory of Myers and Majluf (1984).

The vast majority of the papers I analysed focus on large publicly traded companies. It is my intention to follow this framework in my research, part of the reason being that information on small companies may not be readily available or accurate for my research.

In the research paper by Giannetti (2003) “Do Better Institutions Mitigate Agency Problems? Evidence from Corporate Finance Choices”, the author argues that the failure to find a significant impact of country-specific variables may be due to the bias induced in many researchers only using large firms data in their studies. As it data for developing countries is hard is obtain this may be a limitation on the results I find. A large sample of unlisted firms are analysed from eight European countries and finds a significant influence on the leverage of individual firms of a few institutional variables such as legal system, stock market development and credit protection laws.

After reviewing the papers I have made the following hypothesis:

Asset Structure will be positively related to debt in both developing and developed countries

Firm Size will be negatively related to debt in both developing and developed countries

Growth will be positively related to debt in both developing and developed countries

Profitability will be negatively related to debt in both developing and developed countries

Section II. Data and Methodology

In this section I will describe the data set, how it was collecting and some problems that occurred while obtaining the variables. I will then go on to describe the variables used and the way I will go about obtaining my results.

Data

For this research, I have collected data from the top 200 companies in terms of market capitalization in USA, UK, Germany, Japan, Brazil, Russia, India and China. Of the eight countries four are developed countries (USA, UK, Germany and Japan). The other four are the BRIC countries (Brazil, Russia, India and China). The BRIC countries are considered to be developing countries. The top 200 organisations were chosen as I deem it to be an adequate amount to allow accurate and significant results to be found.

Osiris banking system is used to obtain information about the top 200 firms in terms of market capitalization for each country. This paper assumes all the information on Osiris is correct and up-to-date. From Osiris banking system the following variables were exported for each of the eight countries: Company Name, Total Asset of Firm, Long Term Debt of Firm, Fixed Assets of Firm, EBIT (earnings before interest and taxes) of Firm, Sales of Firm, and Total Assets of previous year of Firm. These will be used to calculate my independent variables.

Problems Collecting Data

I had intended to have an even number of companies of each country. A number of the companies, specifically those of developing countries have dropped from the data set due to missing information on the firm. This explains why some of the countries have few observations than others. Any large outliers in specific countries have also been removed from my sample. Another problem that occurred when collecting my data, which may have influenced my results, is that each country has different year ends and that at a particular point in time it is hard to determine if the data is as recent for some countries. By using the top 200 firms across the 8 countries I will hopefully be alleviating any corporate governance issue as most of these companies will be facing the same issues regarding this area. By only using the top 200 firms and not an aggregate level of leverage across each country it could be seen that my sample is somewhat bias.

Independent Variables

According to Harris and Raviv (1991), “leverage increases with fixed assets, non-debt tax shields, investment opportunities, and firm size, and decreases with volatility, advertising expenditure, the probability of bankruptcy, profitability, and uniqueness of the product.”

A number of these variables are difficult to accurately quantify and therefore this study is limited to four variables. These are asset structure (tangibility), profitability, firm size (log of sales) and investment opportunities (growth). These are the four firm specific variables that Rajan and Zingales (1995) found to be the most significant in affect capital structure choices.

Dependent Variable

The dependent variable is the leverage variable as the main aim of this paper is to determine the main drivers that influence leverage in a firm. Leverage within a company is commonly referred to as the ratio of total liabilities to total assets. Many of the research papers in read used a number of different leverage variables and compared the changes. Different measures of leverage are listed below and some description of what Rajan and Zingales (1995) believed about this measures.

Ratio of short term debt to total assets; only includes short term liabilities without considering the long term debt position of a firm

Ratio of long term debt to total assets; a good proxy for leverage as it does not include short term debt which changes frequently

Ratio of Total debt to total assets; doesn’t not include liabilities like untaxed reserves or accounts payable and is seen to be a great measure of leverage although it is affected by level of trade credit.

Total liabilities to total assets; commonly recognised as the broadest definition of leverage. The measure is perceived to be a proxy for what is left to shareholders in the case of bankruptcy. It is not a good indicator of whether a firm is at risk of default as it may overstate the firm’s actual leverage by including items that have nothing to do with financing.

I have chosen to use the ratio of long term debt to total assets as I believe that I will get the most significant results from this ratio. Short term debt can often be hard to determine accurately and therefore affecting the total debt variable also.

Regression Equation

My regression equation is:

LEVERAGE = β0 + β1TANG + β2 PROFIT + β3 SIZE + β4GROWTH+ ε

From the data I exported from Osiris the following new variables are created to be regressed.

Leverage: Ratio of long term debt to total assets

Tangibility: Ratio of fixed assets to total assets

Profitability: Ratio of EBIT to total assets

Sales: Log of Sales

Expected Growth: (Total Assets of Firm - Total Assets of previous year of Firm)/ Total Assets of previous year of Firm

Methodology

Firstly this study will go about answering the first research question stated in the introduction of whether leverage differs significantly across countries. To do this there will be analysis the leverage ratio figures in each of the eight countries. Following on from this, the paper tackles answering the second and third research questions of determining whether there are differences in how the determinants of capital structure change across countries. The paper follow the regression stated above of the data for each of the eight countries. The first set of regressions that are run are regressing each country separately to give determinant results of each individual country then the regressions with all data of developed countries and compare it to those of developing countries.

These regressions will be run on STATA econometrics software. STATA is a great tool as it produces results including R squared values, p-values and tests if the results are significant. My result would be very difficult to obtain without the use of this software.

After the regressions are run and exported to excel format the results are examined. Firstly, by checking how significant the results are. Subsequently studying the p-values and R squares of each of the dependent variables across the countries to establish whether or not the influence they have on firm capital structure is actually significant as well as comparing my findings to other literature.

Section III. Results and Analysis

In this section aims to answer the research questions which involve cross-sectional analysis of all of the eight countries. The first research question asked how capital structure differs across countries. Table 1 show the summary of the leverage ratio statistics across the eight countries. From this I can analysis the difference in leverage across the countries.

Table 1. Leverage Ratio Statistics

Table 1

Leverage Ratio Statistics

Mean

Std.

Min

Max

Obvs(N)

Brazil

0.20438

0.135792

0.000878

0.628786

156

Russia

0.160883

0.126526

0

0.541229

118

India

0.297377

0.272002

0

2.539287

146

China

0.140194

0.115018

0.000048

0.505532

160

USA

0.213288

0.130156

0.000958

0.702959

155

UK

0.224359

0.151857

0.000225

0.620624

142

Germany

0.188601

0.153208

0.000488

0.736682

154

Japan

0.194557

0.145336

0

0.628246

167

It shows the number of observations (N) in each of the countries, the mean, standard deviations (Std.), minimum and maximum of the leverage. From the table it can be seen that there is some differences in the average leverage across countries. India has the largest ratio of 0.297 but it also shows a large deviation among the companies with a standard deviation of 0.272 and a maximum of 2.539287. This means that on average a firm in India will have 27% of its assets as long term debt. In the case of the maximum 254% leveraged against its assets. All other countries have similar mean leverage ratios with the range between 0.140 in China to 0.224 in the U.K. Hale (2007) found evidence which suggested that China’s bond market is limited in both scale and capacity, this could be a potential reason why China has slightly less leverage than USA and UK which have well developed bond markets. It is not a question of economy size as China recently over took Japan as the second largest economy in the world.

Table 2 shows the summary statistics of the independent variables; Tangibility of assets (Tang), Log of sales (Size), Profitability (Profit) and Investment opportunities (Growth).

Table 2. Summary Statistics of Variables Means across each Country

Table 2

Summary Statistics

Leverage

Tang

Size

Profit

Growth

USA

0.213288

0.653882

16.81205

0.119306

0.099136

UK

0.224359

0.670681

15.09034

0.095787

0.103438

Germany

0.188601

0.540166

14.57779

0.065996

0.063012

Japan

0.194557

0.581782

16.25403

0.041487

0.083993

Brazil

0.20438

0.573561

13.76095

0.073483

0.814849

Russia

0.160883

0.640311

14.0233

0.083398

0.102352

India

0.297377

0.554198

13.86988

0.115142

0.403165

China

0.140194

0.517808

14.2507

0.080161

0.313357

Looking at the statistics on the four determinants of capital structure we can see the mean of the variables are fairly similar across the eight countries. The largest average firm size is the United States with 16.81. This is something the does not come as a shock as most big firms have their headquarters in the U.S. Investment opportunities (growth) are bigger in developing countries in particular Brazil with 0.815. This is logical as these countries are in emerging markets with a more growth prospects compared to established firms in developed countries.

Regression Results of 8 Countries

LEVERAGEcountry = β0 + β1TANG + β2 PROFIT + β3 SIZE + β4GROWTH+ ε

Table 3 shows the results from running the linear regression (OLS) on all of the eight countries, using the data gathered from Osiris. A robust OLS regression method is used to obtain the results. As previously stated the dependent variable for leverage used is long-term debt to total assets as I believe it will most significant measure of leverage and thus produce good results. Table 3 includes the co-efficient (β) of each of the variables in the 8 countries. Also included in the Table 3 is the intercept (β0), number of observations and the R squared figure for each regression. The p values in the table will help establish of the significance of the variables.

Analysis of my findings

R squared figures range from 0.495 in Japan to 0.024 in Russia. The R squared values shows how good the model is and how well the variables explain the dependent variable. Even though there is a few low R squared values (Russia 0.024 and Brazil 0.082) the figures on a whole are reasonable and I believe that finding from these results are still significant. Table 4 shows the sign of each variable showing whether it has a positive or negative effect on firm leverage. Thus a minus (-) indicates that the variable has a negative relationship with capital structure and a plus (+) indicates that it has a positive relationship in a particular country. Also the asterisks indicate whether the co-efficient was significant. The p-values are very low which would also lead me to conclude that the results are significant. Analyse of each of the determinants and what effect they have upon leverage in each of the countries follows, using Table 3 and Table 4.

Asset Structure (Tangibility)

The results indicate a positive relationship between tangibility and leverage. This confirms the first hypothesis that asset structure will have positive affect leverage across both developing and developed countries. This finding that tangibility has a positive effect on leverage is consistent with the results found by Rajan and Zingales (1995) as well as Van deWijst and Thurik (1993). They suggest that fixed assets are generally considered to have more security than current assets. Thus firms with more tangible assets should issue more debt. 5 out of the 8 countries show strong statistical results with very low p-values.

Although all countries exhibit positive relationship, developing countries seem to be less influenced by asset structure than developed suggesting that tangibility of assets is not as big a factor in the developing world. For example Japan’s tangibility variable being 0.481 compared to that of Russia’s 0.0466.

Size

Results of firm size show an ambiguous conclusion, there is no strong relationship between size and leverage across the countries. As seen in table 3 the size variables are all relatively small. This does not prove the second hypothesis that firm size will be negatively related to debt in both developing and developed countries. What has been found is that there is no significant difference in the way the size effects capital structure between developing and developed countries.

I would like to point out that the companies sampled are all of the top Market capitalization of each country and therefore different business needs for each company regardless of size may influence the results of leverage as they are all relatively large companies. As these are large companies they should be more capable to issue securities like equity, and should have lower debt. This is especially true in countries with well developed capital markets. This differs from the findings of Rajan and Zingales (1995). They believed that size acts as an inverse proxy for the probability of default. An increase in company size would lead to a decrease in the probability of default of a firm. This would mean that the bigger firms are the easier they will find it to obtain debt thus explaining the positive relationship between firm size and capital structure.

Profitability

From table 3 and 4 this paper concludes that there is a negative relationship between profitability and leverage in 7 of the 8 countries. USA has exhibited a positive relationship of 0.0229 but this finding has no shown to be significant at even the 10% level. Asia countries seem to have a greater negative relationship (Japan -0.632 and India -0.87) but this is not between developing and developed countries. This follows the third hypothesis that profitability will be negatively related to debt in both developing and developed countries.

This goes along with the pecking order theory, which is based on works by Myers and Majluf (1984) and Booth et al. (2001). They suggest that firms have a pecking-order in the choice of financing their activities. This theory states that firms prefer internal funds rather than external funds. This is would that the more profitable a firm is the less prone it would be to take on debt but use their own profits to finance decisions. My results contradict the theory put forward by Jensen (1986) as Jensen suggests that profitable firms will be forced to take on debt to help combat the moral hazard effect that there is between managers and shareholders. By making managers have debt repayments it will to some extent a line their interests to that of the shareholders and prevent employee shirking.

Growth

There is no consensus result to show how investment opportunities affect capital structure decisions. This does not prove the fourth hypothesis that Growth will be positively related to debt in both developing and developed countries.

USA and UK show significant negative relationship between growth and leverage (-0.14 and -0.76 respectively) which follows on from Booth et al (2001) which suggest a negative relationship between his market-to-book ratio (proxy for investment opportunities) and leverage. It has been argued by Myers (1977) that high growth firms will face difficulties in borrowing as they may be relatively new and of greater risk than other industries causing the need from investors to require greater interest payments in return. In contrast China has shown a significant positive relationship (0.0537) which coincides with logic that would lead us to believe that there will be a positive relationship between growth and leverage since growth opportunities implies a need for extra funds.

From the Table 3 and 4 I have been able to see the difference between the countries, I will now analysis the developed countries against the developing countries. The following table shows the regression results for both developed and developing countries. I have used the same regression equation shown below;

LEVERAGEDeveloped = β0 + β1TANG + β2 PROFIT + β3 SIZE + β4GROWTH+ ε (1)

LEVERAGEDeveloping = β0 + β1TANG + β2 PROFIT + β3 SIZE + β4GROWTH+ ε (2)

Table 5 shows a great comparison between the developed and developing countries determinants of capital structure. The R squared is good in developed countries data (0.263) but not high in developing countries data (0.048). That is why there will also be referral to Table 3 and 4 to draw significant conclusions between the two groups of countries.

It can be seen that asset structure has a positive relationship on leverage on both developed and developing countries (0.368 and 0.078 respectively). This was something that was seen in the individual analysis of countries in table 3 and 4. The results are significant at the 5% or greater level. This reaffirms the hypothesis of a positive relationship between leverage and asset structure.

Size has shown to have a small negative effect on both developing and developed countries. The size results have not shown to be as significant as others. From the size results I can conclude size is not a good indicator for leverage does not only differ across countries but across industries as a whole.

Profitability has shown a significant negative correlation to leverage across both developed and developing countries (-0.141 and -0.341 respectively). This proves that across countries the more profitable of a firm the more inclined they are to finance through internal funds than through debt. As previously said this follows with the pecking order theory and the work of both Myers and Majluf (1984) and Booth et al. (2001).

Again investment opportunities have given an ambiguous result on how it affects leverage of firms. In developing countries a slightly positive relationship and in developed countries a negative relationship. I don’t believe there is significant difference to say that developing countries differ drastically in the how investment opportunities affect the choice of debt decisions. It could be argued that after the recent financial crisis banks and other financial institutions are still reluctant to lend to companies, especially those of high investment opportunity that is why in such countries as USA a negative relationship can be seen as the opportunity to take on more debt will be at a higher cost than it would have been before the financial crisis.

Section IV. Conclusion

Throughout this paper I believe I have been able to show that the determinants of capital structure do not differ significantly between developed and developing countries but that firm specific factor play a bigger role in determining how levered a firm is. This paper has answered the three research question at the start.

This study shows highly significant results to show that across all 8 of the countries analysed tangibility has a positive relationship with leverage and profitability has a negative relationship with leverage. In addition that growth and firm sizes do not influence capital structure in a major way in either developing or developed countries.

I can say with confidence that the results are consistent, although there are some weaknesses to the research which could be addressed if I am going to conduct further analysis in this field. As this empirical project only examined the top 200 market capitalized firms in each country, a larger dataset of firms may give more accurate results for the average level of countries leverage. In addition I believe that further examination into other determinants of capital structure and how they differ across countries. This could be done by including variables that I deemed difficult to measure tax shield, company risk, the level of concentrated ownership, advertising expenditure, probability of bankruptcy, and uniqueness of the product and liquidity. Separating the firms into specific industries and analysing the different industries and how the determinants affect them across countries could be an interesting way of investing both firm specific effects along with country specific factors.

By applying dynamic panel data regression in future research may make it possible to reveal fascinating relationships between short and long-term leverage, contrasted over a number of years.

The results in this paper may also be influenced by endogenous variables. The independent variable may be correlated with each other. It is likely that the amount of tangible assets increases as the size of the firm increase. Furthermore the profitability of a firm as likely to increase as sales (proxy I used for firm size) increases. It is therefore suggested, that future research takes endogeneity into account and helps to alleviate it from the findings, by using a different econometric model.

In conclusion, this paper has found that the determinants of capital structure do not significantly differ between developed countries and developing countries. Profitability has a negative on capital structure in all 8 countries and tangibility of assets has a positive effect on leverage in developing and developed countries. Firm specific factors play a great role in influencing how firms are financed.

Section V. References

Booth, L., Aivazian, V., Demirguc-Kunt, A., Maksimovic, V. (2001), “Capital Structures in Developing Countries”, Journal of Finance, 55: 87-132.

Demirguc-Kunt, A., and Maksimovic, V. (1999), “Institutions, Financial Markets and Firms’ Choice of Debt Maturity”, Journal of Financial Economics, 54: 295–336.

Fama, E., and Jensen, M. (1983), “Separation of ownership and control”, Journal of Law and Economics, 26: 301-325.

Giannetti, M. (2003), “Do Better Institutions Mitigate Agency Problems? Evidence from Corporate Finance Choices”, Journal of Financial and Quantitative Analysis, 38: 185–212.

Hale, G. (2007). “Prospects for China’s corporate bond market”, Federal Reserve Bank of San Francisco Economic Letter: Pacific Basin Notes No. 07.

Harris, M., and Raviv, A. (1991), “The theory of capital structure”, Journal of Finance 46: 297-355.

Jensen, M. (1986), “The Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers”, American Economic Review, 76: 323-329.

Jensen, M,. and Meckling, W. (1976), “Theory of the firm: Managerial behaviour, agency costs and ownership structure”, Journal of Financial Economics, 3: 305–360.

Modigliani, F,. and Miller, M. (1958), “The cost of capital, corporation finance and the theory of investment”, American Economic Review 48, 261-297.

Modigliani, F,. and Miller, M. (1963), “Corporate income, taxes and the Cost of Capital: A Correction”, American Economic Review 53: 443–53.

Myers, S,. and Majluf, N. (1984), “Corporate finance and investment decisions when firms have information that investors do not have”, Journal of Financial Economics 13: 187-221.

Myer, S. (1977), “The determinants of corporate borrowing”, Journal of Financial Economics 5: 145-175.

Myers, S. (1984), “The capital structure puzzle”, Journal of Finance 39: 575–592.

Rajan, R. G. and Zingales, L. (1995), “What Do We Know about Capital Structure? Some Evidence from International Data”, Journal of Finance, 50: 1421-1460.

Titman, S., Wessels, R. (1988), “The determinants of capital structure”, Journal of Finance 43: 1–19.

Van der Wijst, N., and Thurik, R. (1993), “Determinants of small firm debt ratios: an analysis of retail panel data”, Small Business Economics, 5: 55-6

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