Do institutions matter? A global perspective
on capital structure
By R.W. Mak
Supervisor: Dr. H. Vrolijk
Co-assessor: Prof. dr. L.J.R. Scholtens
University of Groningen
Msc International Financial Management
June 2014
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ABSTRACT
In this study I examine the effects of the institutional environment on the capital structure of 2886 listed firms from 23 countries. The results suggest that the institutional environment does affect the capital structure of firms, but overall the explanatory power of institutional variables is low in comparison to firm level factors. Factors found to have a consistent significant effect are creditor and shareholder right protection, enforcement, stock market development and development of the domestic banking sector are consistent predictors of the leverage ratio. Furthermore, firm level variables identified by prior research as determinants of capital structure, such as asset tangibility, size and profitability have been confirmed as significant predictors by this study.
JEL Classification: G32
Keywords: Capital structure, institutional environment, leverage, debt financing
CONTENTS 1. INTRODUCTION ... 3 2. LITERATURE REVIEW ... 4 2.1. Literature overview ... 4 2.2. Hypotheses ... 8 2.2.1. Legal system ... 9
2.2.2. Banking sector and capital market development ... 11
2.2.3. Taxes ... 12
3. DATA & METHODOLOGY ... 14
3.1. Sample ... 14 3.2. Dependent variables ... 15 3.3. Independent variables ... 16 3.4. Control variables ... 16 3.5. Descriptive statistics ... 18 3.6. Model specification ... 22 4. RESULTS ... 23
4.1. Firm level effects ... 23
4.2. Country level effects ... 26
5. CONCLUSION ... 28
REFERENCES ... 31
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1. INTRODUCTION
Over the last decades, the financing decisions of firms have been a popular research subject in the field of corporate finance, giving ground to various theoretical models which attempt to explain corporate financing behaviour, i.e. the mix of debt and equity used to finance its assets and investments. Earlier studies have predominantly focused on the effects of firm characteristics, ignoring the environment in which the firm operates. As several later studies have shown, differences in legal system, banking sector and capital markets do matter for corporate financing decisions. It is important to understand the institutional forces driving financing and capital structure decisions because it allows us to better explain the patterns that exists around the globe and how firms behave in different environments. Although it is now accepted that the capital structure of firms is also influenced by the institutional
environment in which it operates, the effect of the environment remains a grey area, because existing empirical evidence is not consistent. A possible explanation for the lack of
concluding evidence is that the existing literature is primarily focusing on a single or small set of countries concentrated in the same region or are selected based on similar
characteristics (Booth, Aivazian, Demirgüç-Kunt and Maksimovic, 2001; Giannetti, 2003; Bancel and Mittoo, 2004). Hereby they only capture a small part of the variation in
institutional environments that countries can have, making it difficult to generalize the findings of the results. Moreover, as Booth et al. (2001) mentions, differences in accounting systems can make it difficult to compare financial statements across countries, potentially causing the mixed results found in studies comparing large international datasets.
In order to address these issues I will examine the effects of the institutional
4 markets. The third group consists of indicators that have to proxy for the size of the domestic banking industry, including private credit to GDP and total assets of the domestic banking industry. And to conclude the effect of taxes will be taken into account. Additionally, firm level determinants that have been identified as determinants of capital structure in prior research such as size, risk, growth opportunities, profitability and asset tangibility will be controlled for.
The results show that differences in the capital structure of firms can partly be explained by differences in the institutional environment, although the marginal explanatory power of institutional variables is relatively small in comparison to the firm level variables. More specifically, the results suggest that firms in countries with a large banking sector use more debt, whereas a highly developed stock market has the opposite effect. In regards of the legal system, effectiveness of the judicial system and creditor rights have a negative effect on the amount of debt used by firms, in order to avoid situations of financial distress imposed by creditors. Furthermore, if shareholders are well protected the amount of available equity financing in the economy increases and consequently firms tend to use less debt financing in such an environment. In contrast to the results of earlier studies (i.e. Booth et al., 2001), I have not found evidence that the tax advantage of debt has a significant effect.
This paper will continue with a review of the existing literature on the subject. Followed by the introduction of the hypotheses to be tested. In the third section of this paper the data and methodology will be discussed. Afterwards, the results will be presented and discussed, followed by the conclusion of this paper.
2. LITERATURE REVIEW
In this section the existing literature on firm leverage will be discussed. Hereafter, I will discuss the institutional factors that I am going to examine. Furthermore, this discussion will also lay the foundation for the hypotheses that will be tested in this paper.
2.1 Literature overview
5 2001). A common way to define capital structure is by looking at the leverage ratio of firms (Rajan and Zingales, 1995; Giannetti, 2003; Deesomsak, Paudyal and Pescetto, 2004; De Jong 2008). The literature has come forward with several alternative definitions for leverage, measuring the extent to which firms use debt to finance its assets. However, they differ in both the type of debt considered and how it is measured, i.e. using the book or market leverage. The focus of the older literature has been primarily on book debt ratios while more recent studies are also considering market debt ratios. Book ratios are conceptually different from market ratios because book ratios are resulting from accounting and are generally looking at historic costs while market values are determined by looking forward in time, at what the asset would sell (Frank and Goyal, 2009). Therefore, for firms with assets that appreciate or depreciate heavily, using the book value may not be representative for the actual amount of leverage the firm carries. Hence, many recent studies opt to include both the book and market ratio in their analysis to cover for these effects and to check the robustness of their findings (De Jong et al., 2008; Frank and Goyal, 2009). Moreover, studies differ in the type of debt they consider, i.e. using a total debt measure or long term debt ratio.
However, most studies choose to use both a long term debt and total debt ratio in order to be able to better interpret the results. In this study I will follow the line of Booth et al. (2001), Giannetti (2003), De Jong et al. (2008) and Frank and Goyal (2009) by defining leverage in terms of a total debt, long term market and book debt ratio to measure leverage.
The first studies that examined determinants of capital structure focused primarily on properties of the firm itself, such as firm size and growth rate. Titman & Wessels (1988) have analysed the effect of firm level variables on leverage and found evidence that firms with unique or specialized products have lower leverage ratios in comparison to firms who do not have these products in their portfolio. Furthermore, they found that small firms use relatively more short term debt, consisting of any debt that is due within one year. However, for other variables such as the expected growth rate of the firm, non-debt tax shields,
6 While most research on capital structure decisions, as introduced above, is based on a dataset from one country, or from similar countries, focusing on firm level variables such as firm size, risk, expected growth rate etc., only a few studies have attempted to make a cross country analysis, attempting to resolve how differences in the institutional environment influence the capital structure. In the context of capital structure theory, most authors refer to the institutional environment as the body of laws and regulations in place, the development of the capital markets and financial sector, and the fiscal environment. Development of capital markets is an abstract concept for which the theory does not have one unique
definition. Current models suggest that capital market development is a multifaceted concept (Demirgüç-Kunt and Levine, 1996). Hence, the literature has come up with several
indicators, such as market size (De Jong et al., 2008; Booth et al., 2001; Giannetti, 2003), liquidity (Hall, Hutchinson and Michaelas, 2004) and market concentration (Levine and Zervos, 1996). However, there is not a comprehensive measure of capital market
development that covers all aspects. Therefore, I use total market size, which is measured as total market capitalization relative to GDP as a proxy for the development of capital markets, following earlier research (Rajan and Zingales, 1995; Booth et al., 2001; De Jong, 2008; Song, 2004; Giannetti, 2003). This will also enable me to better compare the results against earlier studies.
One of the first studies which used a large international dataset to analyse the effects of the institutional environment on capital structure was conducted by Rajan and Zingales (1995), studying the capital structure of firms from the former G7 countries1. From their research it became apparent that the firm level factors that were identified in prior research to be related to leverage are similarly related across the countries. However, only a small part of the variation in the observed leverage ratios could be explained by their model and they concluded that the current models do not suffice in explaining cross country variation and therefore a deeper understanding of the effects of institutional differences is needed (Rajan and Zingales, 1995).
Building on this research, Booth et al. (2001) has focused its research specifically on the effect of country level determinants on firm leverage in ten developing countries.2 They found that firm level variables relevant for explaining capital structures in developed
1 G7-Countries: the United States, Japan, Germany, France, Italy, the United Kingdom
(Rajan and Zingales, 1995).
2 India, Pakistan, Thailand, Malaysia, Turkey, Zimbabwe, Mexico, Brazil, Jordan, and Korea (Booth et al.
7 countries (i.e. the United States, and Europe) are also relevant in developing countries,
despite large differences in the institutional environment of these countries. But are sceptical about the influence of the country factors they examined, i.e., GDP growth rates, inflation rates, development of capital markets and size of the banking sector. Because the overall impact of the variables is low and the signs are not consistent and sometimes vary over countries. They suggested that this could be due to sample size differences, but it could also imply that other institutional factors, such as differences in accounting systems and hereby preparation of financial statements, affect the importance of the variables they analysed (Booth et al., 2001).
Similarly, Song (2004) found that most variation in capital structures is the result of heterogeneity of firm, industry and country specific determinants, but are questioning the role of the legal system in explaining variations in capital structure as depicted in other studies. More specifically, they could only find evidence for the effects for country specific macro factors as GDP growth, size of the banking sector, stock market development and creditor protection. This result is in contrast with other studies (Booth et al., 2001; Giannetti, 2003; De Jong et al., 2008) who have also identified other aspects of the legal system as significant, such as effectiveness of the legal system and shareholder right protection.
Furthermore, this study has attempted to explain variations in capital structure in terms of the legal origin of a country, i.e. common or civil law, but found that this is not an effective factor in explaining cross country deviations in capital structure.
Giannetti (2003) argues that earlier studies could not find conclusive evidence
because they only include large corporations in their dataset. This can affect the results found because large firms often have access to international capital markets and therefore their financing decisions are less subject to the institutional constraints imposed by the domestic market. Therefore she uses data from 8 European countries from small unlisted firms.3 She
did find evidence that attributes of the legal system, i.e. the level of creditor right and shareholder right protection, and bond market development, were significantly related to leverage. Hall et al. (2004) have conducted a similar research, focusing on unlisted firms from eight European countries. They observed cross country variation in the determinants of capital structure and similarly suggest that this is due to the differences in the firms’
institutional environment. However, a remark on these articles should be made. By only
8 focusing on unlisted firms the results of these studies cannot be generalized to listed firms and therefore the results should be interpreted with caution in the context of this study.
De Jong et al. (2008) have suggested that the institutional environment also has an indirect effect on leverage as well, through its effects on firm level determinants. Although they do note that it is difficult to differentiate between what can be seen as a direct or indirect effect. In regards of the direct effects, the paper has produced mixed results, specifically about the effect of the development of capital markets. They hypothesized that corporate leverage is positively influenced by the bond market development, because corporations have more options to borrow and it increases the amount of debt financing available in an
economy. Similarly, they hypothesized that stock market development has the opposite effect and induces firms to decrease leverage because they face more supply of funding which lowers the cost of equity financing (De Jong et al., 2008). The results suggested that creditor right protection, bond market development and GDP growth have a significant effect on leverage.
From a different perspective, Brav (2009) also points in the direction that the development of stock or bond market is related to firm leverage, although he does not provide direct empirical evidence for this. He argues that underdeveloped stock markets are characterized by low liquidity and less protection of shareholders. These characteristics create an environment in which the value of control (by the owners) and information
asymmetry between outsiders and insiders will be larger, hereby increasing the cost of equity (Brav, 2009). This would imply that firms operating in markets with less developed stock markets are on average more leveraged, as firms rather use debt.
The previous discussion has shown that the literature is unable to provide compelling evidence for the effects of institutional differences on firm leverage and is pointing towards both directions for many of the institutional variables. In the next section the hypotheses that I will test for will be introduced and discussed.
2.2 Hypotheses
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2.2.1 Legal system
Several papers argue that the optimal financing choice is dependent on the information available to investors, their ability to monitor compliance and legal enforcement (Rajan, 1992; Hart and Moore, 1995). As the amount of information available to investors and their ability to protect their investments is dependent on the local legal institutions, it is expected that the capital structure of firms is systematically different between countries (Song, 2004).
An indication of the effective rules in place can be found in the legal origin of a country, that is, English common-law, French civil-law, German civil-law and Scandinavian civil-law. Several studies use a common or civil law classification in order to estimate the legal effects on capital structure, regularity that La Porta, López-de-Silanes, Shleifer and Vishny (1998) have found is that countries with a common law background tend to have a higher level of creditor and shareholder protection, while civil law countries on the other hand tend to protect creditors and shareholders less. But as Song (2004) found this
classification is not effective in explaining cross country variation, because it does not differ between different aspects of the laws and regulations that are relevant, i.e. creditor and shareholder protection. Therefore, in this study I will include these variables separately as indicators for the legal system.
The protection of creditor rights aims to capture certain parts of the local bankruptcy law.4 Providing a measure of how difficult it is for creditors to repossess collateral and
control over the firm if it defaults on its loans and Creditor right protection can affect
leverage in several ways as has been argued in the literature. Giannetti (2003) points out that creditor rights protection makes it easier for firms to obtain loans when they invest in
intangible assets, i.e. R&D, which cannot be used as collateral. Second, from the perspective of agency theory, good protection of creditor rights is important as it can give firms access to long term debt who would otherwise be restricted to primarily short term debt, retained earnings and equity financing. Because in the absence of good creditor rights, creditors may prefer short term debt in order to control opportunistic behaviour by the threat of not
renewing a loan (Giannetti, 2003). This implies that the effect of creditor right protection may be less strong when leverage is defined as total debt ratio, which also includes short term debt.5 Similarly, De Jong et al. (2008) argues that creditors are more willing to provide debt in an environment with better creditor protection. Hence, I hypothesize that creditor right protection is positively related to leverage (Hypothesis 1).
10 As Rajan and Zingales (1995) state, enforcement is a second aspect of bankruptcy law that is important, because it is an integral aspect of a debt contract. While creditor rights gives an indication of the rules and regulations in place to protect creditors, enforcement proxies for how difficult it is to enforce your rights. As they argue, a high level of
enforcement has multiple effects. First, strict enforcement of creditor rights increases ex ante contractibility. Therefore it gives management a strong incentive to avoid situations of financial distress. Second, it commits creditors to penalizing management in case of financial distress. And third, by strictly enforcing creditor rights if the original contract is violated, a long and costly process between claimholders is avoided (Rajan and Zingales, 1995).
The effect of level of enforcement is twofold and not easily predicted. By strictly enforcing creditor rights, the availability of debt financing for firms increases. On the other hand, as Rajan and Zingales (1995) observed, in countries where contracts are most strictly enforced, firms tend to use less debt. They argued that firms maintain low leverage ratios in such an environment because the strict enforcement of bankruptcy law results in too much liquidation of viable firms. This would imply that the second effect is prevailing in this relation. Following this argument, I expect that the level of enforcement is negatively related to leverage (Hypothesis 2).
A second channel through which leverage may be influenced by the legal system is the relation between shareholder right protection and the availability of equity funding. Shareholder rights protection measures the extent to which minority shareholders are
protected by the law and is an aggregate of different rights related to this area. La Porta et al. (1998) have developed an aggregate index of different aspects of shareholder rights,
providing an indication of the extent to which minority shareholders are protected by law in a country. However, after receiving critique from multiple authors for several flaws in the conceptual framework and errors in coding, Djankov, La Porta, López-de-Silanes and
Shleifer (2008) revised the index.6 Minority shareholders tend to be willing to invest more in
countries with good shareholder protection as they recognize that greater profits in the form of dividends can be received, due to more favourable laws, instead of being expropriated by the controlling shareholder(s) (Cheng and Shiu, 2007). Thus, by limiting expropriation, the law raises the price that securities can fetch in the market place raise (La Porta et al., 2002) Hence, increasing the attractiveness of equity financing for firms. Therefore, I expect that in
11 countries with a relatively high level of shareholder protection firms use less debt, thus shareholder protection is negatively related to leverage (Hypothesis 3).
2.2.2 Banking sector and capital market development
The first papers on the subject argue that differences in leverage ratios of firms between countries can be partly attributed to the size of the banking industry and level of capital market development. However, researchers still have not come up with one common concept or measure for this, as it is difficult to grasp all aspects in one measure. Over the years multiple indicators are suggested, such as market size (De Jong et al., 2008; Booth et al., 2001; Giannetti, 2003), liquidity (Hall et al., 2004) and market concentration (Levine and Zervos, 1996). For the purpose of this study, stock and bond market capitalization over GDP (%) proxies for market development, because this is most frequently used in the literature and hereby this increases the comparability of results.
Corporate finance theory suggest that corporations optimally structure financing packages to reduce the economic costs that is caused by taxes and financial market imperfections (Demirgüç-Kunt and Maksimovic, 1996). When markets develop, the
12 the relation between equity market development and leverage is not yet clear and subject for further research.
Similarly, bond market capitalization to GDP (%) is used as a proxy for the level of bond market development. De Jong (2008) argues that firms have more options to borrow when the bond market of a country is well developed. This is supported by Giannetti (2003) who has found that firms are more leveraged in countries with a higher bond market
capitalization, although she points out that this is specifically the case for mature firms and argues that bond market development enhances the access to debt. Therefore, I expect to find a positive relation between bond market development and leverage (Hypothesis 5).
The size of the domestic banking industry in a country can provide information about the influence and level of development of the banking industry, which is important as banks are a major provider of long term debt in the form of loans to firms. They observe that in countries with a large banking sector, firms are more leveraged than firms in countries with a relatively small bank sector. Several studies use the total assets of the domestic banking industry over GDP (%) in order to estimate the importance of banks in a country and find mixed results on this (Song, 2004; Giannetti, 2003). However, as Rajan and Zingales (1995) argue, the ratio of bank loans made to the private sector to GDP (henceforth private credit to GDP) is a better measure, because the results are more consistent. Therefore, I will use these two measures and expect that domestic bank assets and private credit to GDP are positively related to leverage. (Hypothesis 6 and 7).
2.2.3 Taxes
13 and leverage instead. However, as Booth et al. (2001) observe, the effective tax rate is not a proxy for debt tax shield values, but for profitability. Because firms that pay a lower effective tax rate are more profitable, have more retained earnings, and have to use less outside capital to finance investments. Hence, this explains why De Jong et al. (2008) found a negative relation between effective taxes and leverage. This also renders this proxy as unusable for this purpose. Rajan and Zingales (1995) used a different proxy for the debt tax shield effect, the tax gain from leverage formula developed by Miller (1977)7, which also takes personal taxes on equity and interest income into account. However, as they point out, it is difficult to consider personal tax codes in terms of uniformly rates, because tax rates vary depending on the personal situation of the investor, i.e. in which tax bracket is he in. Furthermore,
corporate and personal taxes are under the influence of other regulations, e.g. deductions on taxes according to the source of income. Hence, several assumptions have to be made regarding the appropriate tax rate for the firm and the investor when considering this measure. Song (2004) argues that it is reasonable to use the highest tax rates applicable, because on average investors are more wealthy individuals and fall under the highest tax bracket. Second, it is assumed that firms fall under the highest corporate tax rate, in the absence of one uniform corporate tax rate. Similarly, Booth et al. (2001), Song (2004) and Fan, Titman and Twite (2012) have also used this proxy, but the literature is not in agreement on the relation with leverage. Booth et al. (2001) and Fan et al. (2006) reported a positive relation between this measure and leverage, suggesting that firms use more debt if the tax advantage of debt is larger. However, Song (2004) has not found a significant relation. I will follow the line of these earlier papers and use Miller’s tax gain from leverage formula to proxy for the tax debt shield effect. As the incentive for firms to use debt financing increases when the tax advantage of debt is larger, it is to be expected that firms are more levered in countries having a larger tax advantage (Hypothesis 7).
7 Miller’s tax gain from leverage is calculated using 1 −(1−𝑇𝑐)(1−𝑇𝑒)
(1−𝑇𝑖) where, Tc is the highest corporate tax rate,
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3. DATA AND METHODOLOGY
In this section the data and methodology used will be presented. First, I will discuss how the sample is constructed followed by the definitions of the variables and control variables. Hereafter, the descriptive statistics and regression model will be presented.
3.1 Sample
The data for this paper comes from multiple sources. The sample with firm data was obtained from Orbis and averaged over a period of 3 years, from 2011-2013. From the original
database I filtered for public companies reporting according to the IFRS standards.
Furthermore, financial institutions are excluded because their capital structure is inherently different from normal firms. By including them, this would make the results difficult to interpret. For the same reason state or government firms are excluded as well. Subsidiaries of firms are eliminated because they could potentially bias the results as the parent company is often not from the same country, which could influence the capital structure used. Moreover, only firms with complete data on the dependent variables over this time period are included. After doing so, the sample contains 2886 observations8 from 23 countries9. As this analysis is largely based on ratios, this could result in extreme outliers having very high or low ratios. Therefore, the data is for each country individually winsorized at the 5th and 95th percentile,
8Data required to calculate the long term market debt ratio was not complete for 47 observations, hence there
are 2839 observations for this ratio.
9 After selection, firms from the following countries are included in the sample: Argentina, Australia, Belgium,
Brazil, Canada, China, Colombia, Germany, Denmark, Spain, Finland, France, United Kingdom, Italy, Mexico, Netherlands, Norway, New Zealand, Peru, Philippines, Portugal, Russia, South-Africa.
Hypothesis 1 Creditor right protection is positively related to leverage Hypothesis 2 Enforcement is negatively related to leverage
Hypothesis 3 Shareholder rights is negatively related to leverage
Hypothesis 4 Stock market development is negatively related to leverage Hypothesis 5 Bond market development is positively related to leverage Hypothesis 6 Bank assets to GDP is positively related to leverage Hypothesis 7 Private credit to GDP is positively related to leverage Hypothesis 8 Miller's tax advantage is positively related to leverage This table summarizes the hypotheses for the country specific effects
15 thus requiring all observations outside this bracket to take the value of the nearest
observation within.
The country level data is taken from various sources. Data on the capital markets, banking sector and GDP growth is retrieved from the World Bank Financial Development and Structure (2013) dataset. As the dataset was last updated in 2013, data over this year is not yet included and therefore the period covered is from 2009-2012. The values for Miller’s tax advantage are retrieved from the research published by Fan et al. (2006).
The data on the variables for the legal system are based on the work of La Porta (1998), which provides the data on creditor right protection and efficiency of the judicial system. In the paper they also introduced the anti-director rights index which is a measure of minority shareholder protection. However, this index has received much critique over the years. As Spamann (2006) argues, the results of that study were only strong due to systematic measurement error. Therefore, Djankov et al. (2008) revised the model and came up with a new index, which provides a better approximation of the rights of minority shareholders and is routinely used by cross country studies now. Thus, this index has the preference over the one developed by La Porta et al. (1998).
3.2 Dependent variables
As I have discussed in the literature review, there are several definitions that are used in the literature to calculate the leverage ratio. In this thesis I will follow the research of Demirgüc-Kunt and Maksimovic (1999), Booth et al. (2001) and De Jong et al. (2008), and use three different measures of leverage. First of all, I will use two long term debt ratios, the long term book and market debt ratios, which measure to what extent the assets of a firm are financed by long term debt. These definitions of leverage takes into account that a large part of short term debt usually consists of trade credit. As trade credit is under the influence of different determinants the coefficients can be more difficult to interpret (De Jong, 2008). Arguments for using the book ratio are that it is easier to use and the cross-sectional correlation between book and market value is usually high. Thus the misspecification due to using book values is generally low (Bowman, 1980). However, for firms with assets that have heavily appreciated or depreciated this may be not representative for the true leverage ratio. Therefore, most recent articles (Booth et al. 2001; Giannetti, 2003; De Jong et al. 2008) use multiple
16 definition of leverage that I consider is a total debt ratio, which measures to what extent the assets of a firm are financed by debt, and is calculated by formula (3).
𝐿𝐸𝑉1 = 𝐵𝑜𝑜𝑘 𝑣𝑎𝑙𝑢𝑒 𝐿𝑇𝐷 𝐵𝑜𝑜𝑘 𝑣𝑎𝑙𝑢𝑒 𝑇𝐴 (1) 𝐿𝐸𝑉2 = 𝐵𝑜𝑜𝑘 𝑣𝑎𝑙𝑢𝑒 𝐿𝑇𝐷 𝐵𝑜𝑜𝑘 𝑣𝑎𝑙𝑢𝑒 𝑇𝐴−𝐵𝑜𝑜𝑘 𝑣𝑎𝑙𝑢𝑒 𝐸𝑞+𝑀𝑎𝑟𝑘𝑒𝑡 𝑣𝑎𝑙𝑢𝑒 𝐸𝑞 (2) 𝐿𝐸𝑉3 = 𝐵𝑜𝑜𝑘 𝑣𝑎𝑙𝑢𝑒 𝑇𝐷 𝐵𝑜𝑜𝑘 𝑣𝑎𝑙𝑢𝑒 𝑇𝐴 (3)
Where LTD stands for long term debt, TA for total assets, Eq for equity and TD for total debt. The second measure of leverage (𝐿𝐸𝑉2) considers the long term market debt ratio, where the market value of total assets is calculated as the denominator.
3.3 Independent variables
As introduced in the literature review, this paper will test for six independent variables, being creditor right protection, shareholder right protection, efficiency of the judicial system, bond market development, stock market development, size of the banking sector and taxes. An overview of the definitions of these variables can be found in table II and an extended version in the appendix under table A1.
3.4 Control variables
This section will introduce the control variables used in the model. Those variables have been identified as significant determinants of firm leverage in earlier research (Rajan and Zingales, 1995; Booth et al., 2001; De Jong et al., 2008)
17 Profitability - The pecking order theory suggests that there is a negative relationship between leverage and profitability. The theory argues that firms prefer to raise capital first from retained earnings, second from debt, and third from issuing new equity (Myers, 1984). It is suggested that this behaviour may be seen due to the costs associated with issuing new equity, which arise from information asymmetry and transaction costs. As firms which have been more profitable have a larger amount of retained earnings, this has an effect on the capital structure in the form of a lower leverage ratio for more profitable firms. In order to measure profitability, the ratio of operating income over the book value of total assets is used.
Asset tangibility - Asset tangibility is expected to increase the ability for firms to issue more secured debt, as higher tangibility of assets reduces the risk for lenders. From the
Variable Definition
Enforcement Measures the efficiency and integrity of the legal system, as defined by La Porta et al. (1998)
Creditor right protection Index aggregating different creditor rights, defined by La Porta et al. (1998)
Shareholder right protection Index aggregating different shareholder rights, defined by Djankov (2008)
Stock market development (SMD)
Average of the value of listed shares in percentage of GDP over 2009-2011. Source: World Bank Financial Development and Structure Dataset, November 2013.
Bond market development (BMD)
Average of the value of the total private domestic debt securities issued in percentage of GDP over 2009-2011. Source: World Bank Financial Development and Structure Dataset, November 2013. Size of banking sector
Claims on the domestic real nonfinancial sector by deposit money banks in percentage of GDP averaged over 2009-2011. Source: World Bank Financial Development and Structure Database, Nov 2013.
Private credit Private credit provided by deposit money banks to the non-financial sector as a percentage of GDP, averaged over 2009-2011. Source: World Bank Financial Development and Structure Dataset, November 2013.
Taxes Proxy for the tax debt shield, measured by Miller’s leverage to debt ratio and takes into account personal tax rate on interest and equity income next to corporate tax rate.
GDP Growth Average of yearly GDP growth rate (unit: %) over sample period 2009-2012
Table II Independent Variables
18 viewpoint of static trade off theory, more leveraged firms use more debt because asset tangibility increases the debt capacity of firms because of reduced distress costs (Booth et al., 2001). Hence, in case of a high level of asset tangibility the firm is expected to be more leveraged. Asset tangibility will be measured as the net fixed assets over the book value of total assets.
Growth opportunities – Earlier studies suggest that there is a negative relation between leverage and growth opportunities, due to agency conflicts between stock and shareholders. Myers (1977) argues that firms with high debt levels may forego profitable investment opportunities, because the returns of such a project will be mainly transferred to the creditors instead of shareholders. Similarly, firms with high growth opportunities will avoid the use of debt in order to minimize wealth transfer from shareholders to creditors. Hence, a negative relation between growth opportunities and leverage is expected. Growth opportunities is proxied by the annual change in total turnover.
Risk - If the risk of a firms activities increases, banks become more reluctant to issue credit to the firms. Furthermore, increased risk results in a higher probability of default. Hence, for firms with a high risk profile, debt will be more expensive as creditors demand a higher return for the increased risk of default. Thus, a negative relation between risk and leverage is expected. Risk will be measured as the standard deviation of operating income over the book value of total assets.
GDP growth rate - Following the research of Demirgüç-Kunt and Maksimovic (1999), Song (2004) and De Jong et al. (2008), this paper will use GDP growth rate (%) in order to control for differences in the general economic conditions of a country on leverage.
3.5 Descriptive statistics
The summary statistics for the entire data sample are presented in Table III, which gives an overview of the observations per countries and the mean of the dependent and independent variables. Preliminary analyses of the variables showed that there were signs of
19 N Min Max Mean Median Std. Deviation
2886 0.009 0.551 0.207 0.179 0.157 2839 0.005 0.501 0.175 0.145 0.145 2886 0.063 0.763 0.433 0.442 0.191 2886 0.174 0.924 0.591 0.610 0.220 2885 0.004 0.305 0.070 0.033 0.083 2540 7.784 16.313 12.252 12.353 2.348 2517 -0.278 0.504 0.044 0.031 0.178 2873 -0.379 0.201 -0.001 0.034 0.145 Panel B
Country N Long term book debt
Long term
market debt Total debt Tangibility Size Profitability Growth Risk
Argentina 36 .200 .187 .488 .543 12.190 .075 -.042 .047 Australia 762 .146 .126 .354 .601 11.046 -.058 .003 .111 Belgium 11 .219 .193 .463 .662 13.281 .012 .105 .033 Brazil 87 .322 .277 .521 .598 14.181 .066 .015 .027 Canada 508 .201 .158 .368 .662 11.283 -.060 .070 .095 China 44 .147 .185 .506 .475 13.204 .063 .140 .033 Colombia 8 .150 .168 .275 .727 12.663 .016 .040 .012 Germany 269 .241 .200 .500 .480 12.774 .037 .060 .049 Denmark 55 .191 .161 .472 .550 12.528 .039 .052 .040 Spain 68 .315 .285 .587 .621 13.626 .021 .021 .024 Finland 55 .226 .203 .534 .538 13.620 .041 .060 .034 France 126 .260 .233 .547 .540 13.581 .025 .058 .033 GB 328 .217 .166 .458 .584 12.485 .040 .069 .050 Italy 105 .245 .228 .592 .535 13.098 .018 .040 .034 Mexico 28 .287 .188 .442 .657 14.456 .097 .131 .026 Netherlands 35 .219 .170 .587 .507 13.672 .032 .038 .053 Norway 11 .331 .259 .487 .648 13.283 .043 .107 .051 New Zealand 53 .247 .212 .402 .651 11.638 .030 .037 .050 Peru 69 .211 .246 .398 .666 11.639 .085 .021 .041 Philippines 58 .235 .185 .422 .621 12.116 .066 .152 .048 Portugal 18 .356 .323 .694 .670 13.346 .019 .026 .019 Russia 41 .258 .299 .460 .718 14.658 .064 .046 .042 South Africa 86 .182 .145 .448 .493 12.702 .087 -.043 .051
* Complete statistics on firm level variables per country can be found in the appendix Table 2.
** Correlation matrix including new variables can be found in the appendix Table 3. Table III
Descriptive Statistics
This table presents the descriptive statistics for the variables. Panel A presents the descriptive statistics for the dependent and firm level variables for the complete sample. Panel B shows the mean scores on the firm level variables per country*. Panel C presents the country level statistics. Panel D contains the correlation matrix for all variables.**
Profitability Growth Size Risk Tangibility
Firm level variables
Total debt ratio
Long term market debt ratio Long term book debt ratio
Dependent variables
20
Panel C
Country Efficiency Creditor rights Shareholder rights BMD SMD Private credit Bank
assets Tax GDP growth
Argentina 6 1 0.44 2.67 13.99 12.75 21.58 - 5.23 Australia 10 3 0.79 55.2 111.06 122.42 124.75 0 1.06 Belgium 9.5 2 0.54 53.9 50.08 94.26 115.65 0.03 0.3 Brazil 5.75 1 0.29 22.43 59.3 50.31 85.86 -0.15 2.81 Canada 10 1 0.65 27.25 115.07 128.95 141.14 0.18 1.37 China 6 2 0.78 21.29 73.9 118.05 128.2 0.3 8.64 Colombia 6.25 0 0.58 0.49 57.18 31.17 38.79 - 3.53 Germany 9 3 0.28 30.71 37.77 107.97 129.97 -0.01 3.3 Denmark 10 3 0.47 186.5 60.01 191.18 199.91 0.12 0.29 Spain 6.25 2 0.37 59.61 79.25 209.63 230.72 0.18 -0.88 Finland 10 1 0.46 24.09 47.91 93.29 98.64 0.01 1.28 France 8 0 0.38 55.31 68.01 112.16 130.63 0.17 0.74 GB 10 4 0.93 14.43 118.47 202.4 202.4 0.15 0.28 Italy 6.75 2 0.39 38.19 17.31 115.66 145.67 -0.01 0.24 Mexico 6 0 0.18 16.14 35.61 17.99 34 0.03 2.99 Netherland 10 3 0.21 74.32 70.65 204.24 216.48 0.34 -0.04 Norway 10 2 0.44 32.17 50.91 76.06 78.54 0 0.27 New 10 4 0.95 - 39.23 145.16 150.17 0 0.94 Peru 6.75 0 0.41 3.47 52.45 23.53 25.55 0.3 6.07 Philippines 4.75 1 0.24 0.97 57.48 28.74 43.78 0.33 4.24 Portugal 5.5 1 0.49 59.88 35.01 186.93 200.91 0.17 -0.68 Russia - 2 0.48 - 53.6 42.13 46.41 - 3.69 South Africa 6 3 0.81 19.98 185.43 72.44 82.96 0.32 1.66
Tangibility Risk Size Profit Growth Enforc ement Creditor rights Shareholder rights BMD SMD Private credit Bank assets Tax GDP growth Dependent variables
Long term book debt ratio .264 .053 .337 .101 -.030 -.151 -.111 -.185 -.071 -.159 -.022 .017 .051 .010 Long term market debt ratio .390 .055 .369 .118 -.039 -.215 -.132 -.215 -.059 -.218 -.059 -.018 .013 .066 Total debt ratio -.001 .178 .163 .007 -.055 -.134 -.037 -.149 -.004 -.149 .014 .046 .022 .007
21 The descriptive statistics are subdivided in four parts. Panel A gives an overview of the different measures of leverage, panel B presents the data on the firm level variables per country, panel C presents the statistics for the country level variables and panel D contains the correlation matrix. The number of observations varies drastically between countries, i.e. most observations come from Australia (762 observations) whereas there are less than 20 observations with complete data for other countries. This could potentially introduce a bias if the sample firms are not representative for the complete population of firms in the respective country. Therefore, I have checked the results by excluding countries with few observations, such as Colombia and Belgium, but this did not alter any of the findings and are therefore not reported.
The descriptive statistics on the different measures of leverage show that the average long term leverage ratios differ to a large degree between the countries. Australian firms for example tend to have a relatively low ratio of .146, whereas firms in Spain have a relatively high leverage ratio of .315. Overall, the leverage ratios drop when considering the market debt ratio, which is expected as in most cases the market value of a firm is higher than the book value of its assets. The standard deviation for the long term book and market debt ratios is comparable, implying a similar level of variance in the different measures of leverage. The average total debt ratio in this sample is .433, with a standard deviation of .191. When comparing the total debt to long term debt ratio I observe that countries that have a relatively low average long term debt level, also have less debt in total. This suggests that firms are not substituting short term debt for long term debt in order to finance their operations, but use equity financing instead.
In panel D the correlation coefficients are presented for all variables. The results show that there is no strong correlation between any of the dependent and independent variables. However, when using the market value instead of book value to calculate long term leverage, the correlation coefficients tend to increase for several variables. This could have
implications for the regression results in the form of more significant relations, which I will examine further in the next section. Panel B shows that several country level variables are correlated with each other. First, efficiency of the judicial system, shareholder rights and creditor rights are strongly correlated with each other. Furthermore, efficiency of the judicial system and creditor rights are also strongly correlated with the variables related to the
22 GDP growth, is correlated with several of the other variables. Therefore this may lead to problems when including these variables in this form in the regression analysis. In order to address this potential problem of multi-collinearity, three alternative variables are created by standardizing the observations and taking the average of the respective standardized
variables, leading to the following new variables. Stock market structure is calculated as the average score for stock market development and shareholder protection. Similarly, the bond market structure is calculated as the average from stock market development and creditor rights. As a proxy for the banking sector the average for private credit to GDP and bank assets will calculated.
3.6 Model specification
To estimate the effects of institutional differences on leverage, I use a hierarchical linear regression, a variation of ordinary least squares regression. In this method the variables are added in two blocks, where the first block contains the variables that has to be controlled for and the second block the predictor variables. In the context of this paper these are the firm and country level variables respectively. This method will produce two regression results, the first one containing the firm level control variables, while the second contains the full model including both firm and country level variables. Hereby, the increase in explanatory power by adding the country level variables can be assessed.
The first step consists of running a pooled ordinary least squares (OLS) regression to calculate an estimate of the impact of firm specific variables on leverage. The regression equation can be stated as follows:
𝐿𝐸𝑉𝑖𝑗 = 𝛽0+ 𝛽1𝑆𝐼𝑍𝐸𝑖𝑗 + 𝛽2𝑃𝑅𝑂𝐹𝑖𝑗 + 𝛽3𝑇𝐴𝑁𝐺𝑖𝑗 + 𝛽4𝑅𝐼𝑆𝐾𝑖𝑗+ 𝛽5𝐺𝑅𝑂𝑊𝑇𝐻𝑖𝑗+ 𝜀 (4)
Where, 𝐿𝐸𝑉𝑖𝑗 stands for leverage of firm I in country j. and the independent variables are the
firm level control variables as introduced earlier. .
23 𝐿𝐸𝑉𝑖𝑗 = 𝛽0+ 𝛽1𝑆𝐼𝑍𝐸𝑖𝑗 + 𝛽2𝑃𝑅𝑂𝐹𝑖𝑗 + 𝛽3𝑇𝐴𝑁𝐺𝑖𝑗 + 𝛽4𝑅𝐼𝑆𝐾𝑖𝑗+ 𝛽5𝐺𝑅𝑂𝑊𝑇𝐻𝑖𝑗+
𝛽6𝐸𝑁𝐹𝑗+ 𝛽7𝐵𝐴𝑁𝐾𝑗+ 𝛽8𝑆𝑀𝑆𝑗+ 𝛽9𝐵𝑀𝑆𝑗+ 𝛽10𝑇𝐴𝑋𝑗+ 𝛽11𝐺𝐷𝑃𝑗+ 𝜀 (5)
In this model, the variables for which a high degree of collinearity was determined are
substituted by the new variables BANK (private credit to GDP and bank assets to GDP), SMS (stock market development and shareholder protection) and BMS (bond market development and creditor right protection).
4.
RESULTS
The results are reported in two parts. As introduced earlier in the methodology this paper utilizes three measures of leverage, following Booth et al (2001), De Jong et al. (2008) and Rajan and Zingales (1995). First I will examine the effects of the firm level effects.
Hereafter, I report and discuss the results for the country level variables. As discussed earlier, I use a hierarchical ordinary least squares regression to estimate the effects, which will add the firm and country level variables in separate blocks. In the first block, the firm level (control) variables are added followed by the country level variables. Hereby it is possible to assess the relative contribution of the country level variables to the explanatory power of the model. The results of the regression analysis can be found in Table IV. The regressions are estimated over the full sample as depicted in Table III, where missing observations on the firm level variables are left out pairwise.
4.1 Firm level effects
24
Long term book debt ratio Long term market debt ratio Total debt ratio
Pane l A (Constant) -0.054*** -0.111 *** 0.426 *** -2.321 -5.831 14.797 Tangibility 0.224*** 0.303 *** -0.037 * 12.460 20.404 -1.651 Size 0.028*** 0.026 *** 0.017 *** 15.921 17.775 7.699 Profit -0.050 ** -0.028 ** -0.102 *** -2.018 -2.103 -3.259. Growth -0.003 -0.005 * -0.009 ** -1.026 -1.787 -2.198 Risk -0.004 -0.005 * 0.030 *** -1.106 -1.765 7.672 R² 0.320 0.167 0.055 F-statistic 237.057*** 176.766 *** 30.235 *** Pane l B (Constant) 0.075* 0.044 0.648 *** -1.776 1.286 12.281 Tangibility 0.236*** 0.325 *** -0.012 13.161 22.237 -0.534 Size 0.024*** 0.020 *** 0.011 *** 13.008 13.743 4.855 Profit -0.057 ** -0.046 ** -0.117 *** -2.298 -2.257 3.761 Growth -0.004 -0.005 * -0.009 ** -1.117 -1.870 -2.273 Risk -0.004 -0.005 * 0.030 ** -1.196 -1.797 7.800 Enforcement -0.008** -0.014 *** -0.020 *** -2.372 -5.339 -4.865 Tax advantage -0.028 0.038 0.030 -0.747 1.266 0.650 Banks 0.018*** 0.024 *** 0.033 *** 3.146 5.098 4.493 SM S -0.030*** -0.030 *** -0.030 *** -6.419 -7.999 -5.259 BM S -0.024*** -0.009 * -0.002 -3.772 -1.687 -0.302 GDP Growth -0.006 0.004 0.000 -1.592 1.419 0.016 R² 0.344 0.193 0.084 R² change 0.024 0.028 0.029 F-statistic 119.383 *** 100.780 *** 21.881 *** Table IV
OLS Regression Results
25 they tend to be more leveraged. Furthermore, the results support the expectations that it is easier for larger firms to acquire debt because of the reduced chance of bankruptcy.
Similarly, profitability is negatively related to long term debt and significant when using both the long term book and market debt ratio, confirming the results of earlier studies (Booth et al., 2001; De Jong et al., 2008). The results suggest that firms tend to prefer to use retained earnings to finance investments before using debt or equity financing and are hereby in support of the pecking order theory.
For risk and growth opportunities the evidence is less clear and differs among the measure of long term debt ratio used. Risk is negatively related to the long term market debt, but its significance is low. However, risk is no longer significant under the long term book debt ratio. This is consistent with the results found in earlier studies (Booth et al., 2001; Deesomsak et al. 2004), but conflicting with several other studies (Song, 2004). The mixed results reported in earlier studies and confirmed in this study suggest that the level of risk a firm carries is of limited influence on the use of long term debt. Similar to risk, growth opportunities are only significant when using a market value ratio. The estimated relation is negative supporting agency theory, which predicts that firms with better growth opportunities tend to have less debt in order to not give up on profitable investments due to wealth transfer from shareholders to creditors. However, the estimate for the coefficient is fairly small and only significant at a 10% level, thus the effect is limited in this sample.
Using the total debt ratio changes the results on several variables. Tangibility is significant at the 10% level, but now has a negative sign. This implies that firms with more tangible assets use more long term debt, but overall their debt levels decrease. Therefore the results obtained in this study are consistent with the matching argument that long term assets should be financed by long term liabilities at the expense of short term liabilities.
Furthermore it is in support of the observation made by Booth et al. (2001) that less can be borrowed against long-term assets than from short term assets. Growth, size and profitability all gain in significance while maintaining the same sign as found on the other ratios. The sign of risk is now positive however, where it was negative with the previously used measures, thus reversing the relation according to this model.
26
4.2 Country level effects
When considering the full model in panel B after adding the country level variables, the relations found for the firm level variables do not change to a large extend. However, the sign of tangibility is now negative. Although the estimate is insignificant, this suggests that firms with more tangible assets use more long term debt, but their overall debt ratio remains the same of slightly goes down. Thus, firms are replacing other forms of credit with long term debt as their asset tangibility increases. In regards of the country level variables, enforcement has a significant negative effect on all three different debt measures, hereby confirming hypothesis 2. This suggests that firms tend to have lower levels of debt in countries where the legal effectiveness is higher, because strict enforcement of bankruptcy law results in to many liquidations of viable firms. This effect seems to prevail over the effect of increased availability of debt financing due to increased creditors confidence and willingness to provide long term debt, supporting the argument made by Rajan and Zingales (1995). In comparison to previous studies the results are mixed. As mentioned, Rajan and Zingales (1995) have found a similar relation, but other studies were not able to find evidence for this (Giannetti, 2003; De Jong et al., 2008).
Development of the banking sector (Banks) has replaced the former indicators for the banking sector, domestic bank assets over GDP and private credit to GDP, after I found almost perfect collinearity between the variables. The results show that the development of the banking sector is positively related to long term debt ratio at the highest significance level. The estimate of the sign and effect size is also similar across all three measures of debt, implying that there is a consistent relation between leverage and development of the banking sector. This supports the argument that a better developed banking sector increases the availability of long term debt for firms, thus confirming hypotheses 6 and 7.
27 For bond market structure the evidence is not as clear cut and differs across the
measures used. The relation is significant at the highest and lowest level for the book and market debt ratios respectively. However, in contrast to what I expected to find, the sign of the effect of bond market structure is negative. This means that firms operating in countries with more developed bond markets and better creditor rights, actually use less debt. In order to analyse the cause of this effect I have run regressions with creditor right protection and bond market development separately, but this does not change the results. On both variables a negative relation with debt ratios has been found, although the effect of bond market development was not significant under the market and total debt ratio. Therefore, my results suggest that firms actually avoid the use of (long term) debt if creditors are well protected by law, in order to avoid situations of financial distress, thus rejecting hypothesis 1. In regards of bond market development, the results found are more difficult to explain and
counterintuitive as one would expect to find an increased use of long term debt in the presence of a large private bond market, which exists to facilitate long term debt financing. Hence, hypothesis 5 is rejected. This is also inconsistent with the results reported by Giannetti (2003) and De Jong et al. (2008), who have found a significant positive relation with long term debt usage. However, as Giannetti (2003) observed, the effect of bond market development is only significant for a subsample in her dataset which contains only the largest and mature firms. Hence, this can explain why in a general dataset containing larger and smaller firms as used in this paper the effect was not significant. Furthermore, this indicator is no longer significant when using the total debt ratio. However, this was expected because the total debt ratio also includes short term debt, while bond markets are primarily a
mechanism for long term financing.
The results show that taxes do not have a significant effect on any of the three debt ratios in this sample. Also, the coefficients differ in sign between the three different ratios, implying that there is no relation in this sample. Thus, hypothesis 8 is rejected. This contradicts the findings of earlier research (Song, 2004; Booth et al., 2001). However, as pointed out earlier in this paper, the complexity of tax law makes it difficult to assess the relative tax advantage of debt as it is based on many assumptions, for example regarding the tax bracket the investor is in or specific treatments for firms, which can potentially explain the lack of evidence for this variable.
28 Potentially this is caused by the sample period (from 2009 to 2012) used in this period. As is well known, during this period one of the greatest financial crisis in the past decennia
developed, and accordingly economic growth was reduced to a minimum in many western countries, while upcoming countries were less affected by the economic downturn. Hence, this could explain the negative correlations with several other institutional variables, such as bond, stock and banking sector development. Consequently this could have affected the estimates, due to the abnormal economic conditions in several countries.
The results also suggest that firms use less debt in common law countries, because these countries tend to protect creditor and shareholders the most as La Porta et al. (1998) noticed. This study has shown a negative relation with leverage for both of these variables, contrary to my expectations, thus increasing the availability of equity financing on one side, but also make firms use less debt, in order to avoid situations of financial distress.
Considering the R2 for all three models I observe several interesting patterns. First of all, it seems that the marginal explanatory power by institutional differences is relatively limited. The R² increases to .344, .193 and .084 for the book, market and total debt ratio respectively. However, the effect of adding institutional variables to the model is significant and thus should not be underestimated in studies regarding capital structures of firms. Second, this set of variables is better suited to predict the use of long term debt than total debt. This suggests that short term debt is under the influence of different determinants than the usage of long term debt. Furthermore, the model is not as good in predicting long term market debt ratios as it is for long term book debt ratios. The decrease in explanatory power when using the market debt ratio can be explained as it introduces externalities related to the market into the ratio, hereby increasing the standard error of the estimates.
5. CONCLUSION
In this paper I have examined the effects of institutional differences between countries on the capital structure of firms, by analysing a dataset consisting of financial data from 2886 listed firms originating from 23 countries over the years 2009 to 2012. The findings in this study show that several country specific factors have a significant and consistent effect on
29 order to avoid situations of financial distress. Second, in the presence of a large domestic stock market and an environment in which shareholder rights are well protected, firms use less debt. Third, a large banking sector increases the access to long term debt by providing more loans and significantly increases the amount of debt used by firms. While these conclusions are in accordance with what was expected, this is not the case for creditor right protection and bond market development. From the analysis it can be concluded that creditor right protection has in fact a negative effect on the use of debt, possibly because firms try to avoid situations of financial distress, caused by creditors for who it is easier to repossess collateral and control over the firm. In contrast, I was unable to find concluding evidence pointing to a relation between bond market development and capital structure.
Beside the evidence on institutional factors I have also found that firm specific factors, such as size, profitability and tangibility are significant predictors of the use of debt. Larger firms with more tangible assets that can be used as collateral, generally use more debt, whereas profitability reduces the reliance on debt financing.
This paper has extended the work of earlier studies (De Jong et al. 2008; Booth et al. 2001; Song et al. 2004 etc.) by analysing the effect of country level factors based on a dataset of firms who all report according to international financial reporting standards. Hereby an important argument against the validity of the results obtained by earlier studies is tackled, stating that such an international study is questionable as long as firms use different accounting standards to report in, which reduces the comparability of financial statements. Moreover, this paper contributes to the growing body of research that examines institutional differences and its effects on capital structure, by taking a broad perspective and including 23 countries at different levels of development, while many studies in this area are restricted to a subset of countries.
30 now. Also, this would enable researchers to study the effects of changes in the institutional environment over time.
This study may help management in creating awareness of the environment in which it operates and how this may affect their financing decisions. Furthermore, for policy makers the results show how regulations and other financial institutions affect the financing
behaviour of firms. This enables them to make better predictions about possible implications of new policy and how this may affect businesses in their countries, which is important because a lack of financing options resulting from institutional characteristics may hinder firm growth and hereby the growth potential of the economy.
In conclusion, I have found significant evidence for the effect of several institutional variables on firm leverage, including the effectiveness of the judicial system, development of capital markets and the banking sector. In the process of doing so, I was able to confirm previous results regarding firm level determinants of capital structure. Overall, the evidence provided in this paper shows that country specific factors do matter for capital structure decisions and hence it is recommended that these are taken into account in the analysis of corporate capital structure.
ACKNOWLEDGEMENT
31
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34
APPENDIX
Description of the country level variables
Name Description
Panel A - Legal system
Enforcement This index is an assessment of the efficiency and integrity of the legal environment. Index ranges from 1 to 10, with a higher score implying that is is easier to enforce your rights. Source: La Porta et al. (1998
Creditor right protection This index measures the degree to which collateral and bankruptcy laws protect the rights of borrowers and lenders. Index ranges from 0 to 10, with a higher score implying better protection. Source: La Porta et al. (1998)
Shareholder right protection This index measures the legal protection of minority
shareholders against expropriation by corporate insiders. Index ranges from 0 to 1, with a higher score implying better
protection. Source: Djankov et al. (2008)
Panel B - Capital markets
Private bond market capitalization to GDP
Average of the value of the total private domestic debt securities in percentage of GDP over the period 2009-2011. Source: World Bank Financial Development and Structure Dataset, November 2013. Retrieved from:
http://siteresources.worldbank.org/INTRES/Resources/469232-1107449512766/FinStructure_November_2013.xlsx
Private stock market capitalization to GDP
Average of the value of listed shares in percentage of GDP over the period 2009-2011. Source: World Bank Financial Development and Structure Dataset, November 2013. Retrieved from:
http://siteresources.worldbank.org/INTRES/Resources/469232-1107449512766/FinStructure_November_2013.xlsx
Panel C - Bank sector
Private credit to GDP Private credit provided by depositit money banks to the non financial sector as a percentage of GDP; Averaged over 2009-2011; Source: World Bank Financial Development and Structure Dataset, November 2013. Retrieved from:
http://siteresources.worldbank.org/INTRES/Resources/469232-1107449512766/FinStructure_November_2013.xlsx
Deposit money bank assets to GDP Claims on the domestic real nonfinancial sector by deposit money banks in percentage of GDP; Averaged over 2009 - 2011; Source: World Bank Financial Development and Structure Dataset, November 2013. Retrieved from:
http://siteresources.worldbank.org/INTRES/Resources/469232-1107449512766/FinStructure_November_2013.xlsx
Panel D - Taxes
Miller's tax advantage Measure of how advantaged debt is in comparison to equity financing, taking into account corporate and personal taxes. Index ranges from -1 to 1, with a higher score implying that the advantage to debt is greater. Values retrieved from Fan et al. (2006)
