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Is the capital structure of the multinational corporations (MCs)
significantly different from the domestic corporations (DCs)?
An investigation from BRICS countries firms
By
YONAS KIFLOM TEKLE
Supervisor: Dr. H. Vrolijk Co-assessor: Dr. V. Purice
January 2016
University of Groningen – International Financial Management
Faculty of Business and Economics
Groningen, The Netherlands
Planetenlaan 627, 9742 HW, Groningen,
+31686196411 s2490285
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TABLE OF CONTENT
Abstract ... 3
1. Introduction ... 4
1.1 Multinational corporations (MCs) ... 5
1.2. Multinational corporations from emerging economies ... 5
1.3. Financial crisis ... 6
1.4. Significance of the study ... 6
2. Literature review ... 7
2.1. Theories of Capital structure ... 7
2.2. Firm-specific determinants of capital structure ... 8
2.3. Country-specific determinants of capital structure ... 11
2.4. Literature on capital structure of MCs and DCs ... 12
3. Data and Research Methodology ... 14
3.1. Sample description ... 14
3.2. Data ... 15
3.3. Definition of variables and measurements ... 15
3.4. Descriptive statistics ... 17 3.5. Correlation matrix ... 22 3.6. Model specification ... 23 4. Empirical results ... 24 4.1. Univariate analysis ... 24 4.2. Firm-specific results ... 26 4.3. Country-specific results ... 27
5. Summary and Discussion of results ... 29
6. Conclusion ... 30
Acknowledgments ... 33
References ... 33
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Abstract
This study examines the capital structure of the multinational and domestic corporations based in Brazil, Russia, India, China and South Africa (BRICS). It investigates whether there are significant differences in the capital structure formation and determinants of capital structure over the period from 2003-2014. The results illustrate the average leverage ratios of all BRICS MCs are higher compared to their domestic counterparts for the whole sample period. The empirical study divides the sample period into two parts, the period before the financial crisis (2003-2007) and after the financial crisis (2009-2014). The results show that the average leverage ratio has increased during the post-financial crisis for all MCs and DCs with the exception of India. A detailed observation of the leverage formation of firms shows the leverage ratio of firms differs from country to country. Using multivariate analysis, this study further investigates the firm-specific and country-specific determinants of capital structure. The firm-specific determinants show similarities for multinational and domestic corporations but with varying significance and magnitude. The country-specific determinants are more diverse in their results in both pre- and post-financial crisis periods for multinational and domestic corporations. However, MCs seem to be less influenced by country-specific determinants than DCs. The most consistent determinants of capital structure in the BRICS countries are found to be profitability and tangibility.
JEL Classification: G32
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1.
Introduction
The financial decision on firm's capital structure is one of the most important decisions of any company. This capital structure of a firm is the combination of debt and equity instruments, used to finance the firm's assets. It is the firm’s financial managers’ responsibility to choose the capital structure that minimizes the cost of finance for the firm, thus maximizes the value of the firm. The right mix of debt and equity that maximizes the firm value is commonly referred as the optimum capital structure. However, with a continuously changing dynamics of the financial and business environment, to choose and maintain the optimal capital structure is not an easy task in practice.
Over the past several decades, much of the capital structure research has advanced in developing theoretical models that help to explain the capital structure patterns and decisions. Many of the studies conducted with regard to capital structure and the firm-specific determinants of capital structure have been predominantly with a focus on firms from the United States and European nations such as the United Kingdom, France, and Germany (Antoniou, Guney and Paudyal, 2002). Despite these extensive researches of the understanding and predictability of determinants of capital structure and the theory behind it remains a controversial issue in modern corporate finance.
In the recent decades, there is an increasing research being conducted to assess if capital structure theories hold for all firms across countries; and to investigate if the determinants of capital structure are consistent in determining the capital structure across countries. One of these international studies that compared the capital structure differences between countries of seven advanced industrialized countries conducted by Rajan and Zingales (1995). In their investigation, they argue that several country-specific factors a significant influence on the capital structure of firms across countries. De Jong, Kabir, and Nguyen (2008) have also supported this argument with their extensive documentation on firm-specific and country-specific determinants of capital structure from a large sample around the world.
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international exposure may also present a business or financing opportunity for MCs to get advantage from. With such diversification of business operations, exposures to political and economic environmental influencing MCs capital structure and financing decisions are expected to be different compared the DCs. Previous studies that investigated the capital structure of MCs and DCs show, MCs have lower leverage ratio compared to DCs. (Akhtar, 2005; Akhtar and Oliver, 2009; Titman and Wessels, 1988). However, these examinations have largely targeted MCs originating from OECD countries including Australia, Japan, the US and the UK. This study investigates if these findings can also explain the capital structure of firms from emerging economies or less developed countries.
1.1 Multinational corporations (MCs)
The expression multinational corporations (MCs) does not have a clear-cut definition. For this reason it, it is very important to clearly define the criteria used to categorize MCs and DCs in the study. In categorizing firms, various researchers have used several criteria. The most commonly used measures are foreign tax ratio (Burgman, 1996; Chkir and Cosset, 2001); foreign sales ratio (Singh and Nejadmalayeri, 2004); and the number of foreign subsidiaries a firm has (Tallman and Li, 1996; Errunza and Senbet, 1984). Akhtar (2005) classified firms as MCs if firm’s operations extend beyond the boundaries of the nation where it originally based. In this paper similar to what has been used by Tallman and Li (1996) firms are classified as MCS if they have at least two foreign subsidiaries.
1.2. Multinational corporations from emerging economies
Multinational Corporations from the emerging economies are relatively new phenomena. However, their importance in the global economy has increased in recent decades. According to the report of The United Nations Conference on Trade and Development UNCTAD (2009), multinational firms from emerging economies have increased their share of foreign direct investment (FDI) from 0.4 percent in 1970 to 15.8 percent by 2008. MCs play an important role in the economic development of emerging economies.
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1.3. Financial crisis
For many economies around the world latest global financial crisis was one of the most severe periods. Especially for the developed countries where the financial system and economies are more integrated. It has caused the collapse of several small and big financial institutions, job loss to millions and crashing or creating a volatile environment in the stock markets. In many countries, its impact is still there and have caused a recession or economic slowdown as well. The financial crisis has also affected the BRICS members. However, in comparison, they have come out of the crises rather well. Their economic development has slowed down during the financial crisis period but it quickly recovered in the post-financial crisis period, Despite their fast-growing economies and their significant influence on regional and global affairs, they still have a less developed institutional structures and financial environment compared to the developed countries.
It is important to investigate the existence and sources of finance of MCs and DCs in the context of the emerging economies, this help to understand financing decisions on the firms in those economies. In-depth analysis of the capital structure and determinants of capital structure for MCs and DCs can also give another perspective into the earlier studies from the developed countries on the similar subject. Therefore, it can supplement the studies that have already been conducted trying to understand the determinants of capital structure and their impacts. Furthermore, the topic of global financial crisis has now taken an attention on many finance scholars to investigate its' root causes, impact, and solutions to avoid such crisis in the future. As the world is slowly coming out of the recession the study on the topics is at its early stage. In order to give a hand filling this research gap, this empirical study has also focused on analyzing the capital structure and the determinants for MCs and DCs in the periods of pre- and post-financial crisis.
1.4. Significance of the study
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financial market than their DCs peers. Furthermore, Aggarwal and Kyaw (2008), suggest MC may take comparative advantage over DCs through their capital structure effects. This advantage is highly expected to prevail on firms from emerging markets, where there are more information asymmetries, more market imperfection and lack of efficient governmental and financial institutions. For this reason, MCs from emerging economies may have different capital structure policy and leverage by taking advantage of the ability to get access to international capital markets and be able to get around capital market imperfections. However, comparative studies on capital structure and determinants for MCs and DCs from less developed countries and emerging economies are not substantial.
The purpose of this paper is to examine the capital structure and key determinants of capital structure for MCs and DCs based on BRICS countries. The current study, therefore, attempts to contribute to answering the following research questions: Is the capital structure
of BRICS-based MCs significantly different from DCs? Have the capital structure profile and the determinants of capital structure of MCs and DCs changed after the financial Crisis of 2008/09?
The rest of this paper is organized as follows. The literature review explains, the theories and determinants of capital structure and their impact on firms capital structure. The third section describes the methodology of the study, data collection, and the sample descriptive statistics. The fourth section presents the empirical results, analysis, and discussion. Section five summarizes the key findings and the implications of the study. Finally, section six concludes the paper with suggestions and recommendations for future research..
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Literature
review
In this section, previous literature studies on the capital structure and determinants of capital structure are presented. The first part, discusses the theories of capital structure. The second part presents the firm-specific determinants of capital structure. In the third part, the country-specific determinants are discussed. Finally, evidence and summaries of prior studies on the capital structure and determinants of capital structure for multinational corporations are presented.
2.1. Theories of Capital structure
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arrive at the optimal level of capital structure, several theories have developed. The starting point of all modern theories of capital structure is the capital structure irrelevance theory of Modigliani and Miller (1958). They proposed firm’s capital structure is irrelevant in a perfect world, where there are no capital market imperfections and no possibility of an arbitrage trade. However, the perfect market assumptions of irrelevance theory are far different from the real world in which the firms operate. One departure from the perfect market assumption of the irrelevance theory is the presence of tax. Corporations face a different tax, lending and borrowing treatment and they have to consider for tax shield benefits by raising debt finance. This gave way to Modigliani and Miller (1963) to revise the theory with the inclusion of corporate tax. Further studies that followed this proposition tried to incorporate additional variables and scenarios to show how the capital structure of firms is relevant. These extensions of the study includes that of Miller (1977) on income tax and capital structure, the study on bankruptcy costs by (Titman, 1984), the agency costs of debt Jensen and Meckling (1976), and Myers (1984) informational asymmetry and its impact on the capital structure decisions.
Overall, the studies investigated the costs it has for external financing and the advantages one has to compare in taking capital structure decision. In trying to explain these various determinants of capital structure, it has resulted in the development of the most influential capital structure theories, which are the pecking order theory agency cost theory and the trade-off theory. Introduced by Myers and Majluf (1984) and Myers (1984), the pecking order theory is based on the information asymmetry on the choice between debt and equity. It states that firms have a preferred hierarchy of financing decisions. The first preference is to use internal financing before looking to any other form of an external fund. The traditional trade-off theory puts an emphasis on the benefits and costs associated with issuing debt. Thus, firms with high business risks should use less debt than lower risk firms. This is because; the higher the risk means the higher the probability that the firm will face financial distress (Titman, 1984). The agency theory of capital structure proposed by Jensen and Meckling (1976), argue that an optimal capital structure can be attainable by reducing the costs that are associated with the conflicts between the managers and the owners.
2.2. Firm-specific determinants of capital structure
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between MCs and DCs it is important to investigate on those variables which are found to be most relevant and proven to be significant estimators in previous works of literature. The firm-specific variables used are the growth opportunity, tax, profitability, tangibility, size and firm age. De Jong et al., (2008) have also used similar variables in the study that investigates the cross country difference of capital structure around the world.
Growth opportunity is often defined as the ratio of market value total assets to the
book value of total assets. Higher growth opportunities provide incentives to invest sub optimally or are highly likely to accept riskier projects. This raises the costs of borrowing and, therefore, firms with more growth opportunities tend to prefer internal resources or equity over debt. Therefore, the long-term leverage of a firm is related negatively to growth opportunity. Empirical evidence of the studies by Rajan and Zingales (1995) has also confirmed this negative correlation of growth opportunities and (long-term) debt ratios. While both the static trade-off theory and the agency cost theory predict this negative relationship, the pecking order theory proposes that a positive relationship exists between leverage and growth opportunity. Based on this theory, high growth firms first use the internal financial sources to cover the capital needs of the firm. However, at some point, this internal finance is not enough to sustain more capital needs for future investment need. Consequently, since debt ranks second in pecking order theory before equity, it is expected to increase with increasing growth opportunity in a firm. (Myers, 1984; Frank and Goyal, 2009).
The corporate tax rate is another firm-specific determinant that might influence capital
structure. In theory, firms with a higher effective tax rate would be more inclined to use more debt to increase the tax-shield gain. While dividend payments to shareholders are not tax deductible, the interest payments to lenders are tax deductible. Hence, tax systems typically encourage the use of debt than equity finance. Corporate tax rate is defined as the average tax rate of the year and is calculated as the total income taxes divided by pre-tax income. This measure is chosen instead of the marginal tax rate since concerns the level of debt. According to De Jong et al., (2008) the marginal tax rate explain the incremental change in debt than the debt level itself.
Profitability is another common variable used as a determinant of leverage. It is
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leverage. Several studies have also confirmed that more profitable firms tend to use less debt than the less profitable ones. (e.g Barton and Gordon 1988; Rajan and Zingales 1995; Booth et al. 2001). On the other hand, the trade-off theory predicts profitability and leverage to have a positive relationship. This is for the reason, the more profitable a firm is the lower the expected chance of bankruptcy it has. Therefore, it has a higher capacity to use more debt..
Asset tangibility indicates the amount of collateral a firm can use to secure its debt.
Similar to Akhtar and Oliver (2009), it is measured as the net fixed assets over the book value of the total assets. According to the pecking order theory, the collateralized assets significantly mitigate the information asymmetry and agency cost between lenders and borrowers. Furthermore, the more tangible assets a company has the higher amount that is expected to be recovered from potential bankruptcy or liquidation. Lenders, therefore, require more collateral to secure their loans. Therefore, firms with higher proportions of tangible assets that can be used as collateral tend to borrow more than companies with fewer tangible assets. The Static trade-off theory says that more tangible firms use more debt because of reduced financial distress costs. Based on theoretical argumentation and previous empirical evidence, (e.g. Booth et al., 2001) it is expected tangibility to have a positive impact on leverage. Both theories imply that asset tangibility is positively related to leverage. Hence, the greater the proportion of tangible assets in total assets, the more willing the lenders to supply loans. (Rajan and Zingales, 1995). Empirical evidence of Rajan and Zingales (1995) and De Jong et al. (2008) have also supported the idea that firms rich in tangible fixed assets tend to use more debt.
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Company age is the number of years the firm existed since its establishment. Older firms are generally subject to more news and relatively expected to be more transparent than smaller firms. The investment community would be more concerned and attentive in gathering and providing information about older firms. This makes firms less subject to information asymmetry compared to firms which are younger in age. Thus, they should be more capable of issuing equity which is more sensitive to information asymmetry easily and have lower debt levels. Measured by the natural logarithms of the number of years since its establishment it is expected to have a negative relationship with leverage.
2.3. Country-specific determinants of capital structure
Demirgüç-Kunt and Maksimovic (1999) compared the capital structure of firms from 19 developed countries and 11 developing countries. They found out that the institutional difference between the countries explains the vast variation of the long-term debt. This was also confirmed by the works of De Jong et al., (2008). Country-specific factors can affect corporate leverage in two ways, directly and indirectly through their impact on the effect of firm-specific factors. This paper analyzes the direct impact of country-specific factors, factors like GDP growth rate, stock market development, country capital capacity and law and enforcement. MCs operate across different legal regimes and capital markets around the world making it possible to be affected or identify alternate financing source across countries as opposed to DCs may be more vulnerable to country-specific factors of the country they are based. Among these are the macroeconomic environment, efficiency of legal institutions, and the financial and capital market development. There is some general overlap over which these country-specific variables can be categorized, however, it can explain in the following how they are expected to affect the leverage of at a firm level.
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Institutional environment variable measures the different aspects of governance and regulatory environment that are expected to affect the firm and its stakeholders. The first institutional variable used is same as De Jong et al. (2008) used the effectiveness of the government, which is defined as the perception of the quality of the legal framework to formulate and implement sound policies. This, regulatory quality, captures the perception of the government’s ability to implement policies which stimulate the private sector. De Jong et al. (2008) argues that the institutional and regulatory environment affects the relationship between the firm’s stakeholders and hence the process of corporate governance. The measures for the corporate governance are available from the World Bank database which provides worldwide governance indicators for more than 200 countries for the recent decades. The governance indicators consist of six aggregate dimensions of governance of which four (Legal efficiency, Legal rights, Rule of law and Corruption) are found to be more relevant for this study are averaged to form the variable (Enforcement). This variable measures the protection of lenders and borrowers by the collateral and bankruptcy laws. Giannetti (2003) argues better creditor protection gives firms more access to long-term debt that would otherwise be confined to the use of short-term loans Thus, the enforcement variable is hypothesized to be positively related to leverage.
The financial environment also affects the financing choices of firms. These include the stock market development and the bond market capitalization. The stock market development is measured by the stock market capitalization over the country’s GDP. Demirgüç-Kunt and Maksimovic (1996) argue that firms operating in countries where equity market is highly developed tend to use more equity to finance their investments. As debt is substituted for more equity the leverage ratio of a firm is expected to decline. Therefore, a negative relation to leverage is expected. The opposite effect is true for a country with a more developed bond market.
2.4. Literature on capital structure of MCs and DCs
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in the firm's financing decision; international diversification may enhance debt capacity, and thereby raise the target debt ratio for MCs.
Although there are several gains to be made by moving into the overseas market, a continuous expansion could have also associated risks. The associated difficulties can arise from managing multicultural, multi-location activities and associated political and economic environments and therefore cause an increase in the business risk of the firm. Erunza et al. (1999) have also suggested that, if foreign operations lead to more volatile cash flow firms will like to maintain a lower leverage ratio.
Rego (2003) suggests that the effective tax rate of MCs was significantly lower than of DCs. This observation reflects the ability of MCs to transfer their earnings from high-tax countries to low-tax countries to lower their tax burdens. The ability of MCs to reduce tax burdens may affect the capital structure decision of MCs compared to DCs (Harris et al 1991). According to trade-off theory, the tax shield effect on debt is one of the key determinants of a firm’s optimal capital structure. Firms with a lower tax burden are expected to have lower leverage.
The agency theory may have a different implication for MCs and DCs. Monitoring cost of debt may be higher for MCs due to the complexity and geographic diversity of operational subsidiaries. Therefore, this makes the expected leverage ratio of MCs be lower than DCs. (Lee and Kwok, 1988; Burgman, 1996; Doukas and Panzalis 2003). Empirical studies on US-based firms also show MCs have lower debt to equity ratios compared to their domestic counterparts. As can be seen, in table 2.1 some other studies conducted in other developed countries also confirmed the lower leverage ratio of MCs in comparison to the DCs.
Kwok and Reeb (2000) propose that the relationship between international diversification and capital structure is dependent on the relative risk of the MCs home country and target country. According to this hypothesis, the capital structure of MCs can differ among developed countries based and emerging countries based firms. They provide empirical evidence that international diversification is negatively related to leverage for US-based firms and positively related to leverage for emerging market-US-based firms.
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Table2.1. Summary of Previous Studies on MCs and DCs capital structure
Studied by Countries Period Estimation Method
Dependent Variable
Independent Variable Findings
Lee and Kwok, 1988
U.S. 1964 - 1983
Univariate analyses
LEVERAGE Agency costs, bankruptcy costs, political risk, foreign exchange rate risk
MCs have lower debt ratios
Burgman, 1996 U.S. Panel 1987 - 1991
Panel OLS LEVERAGE agency costs, political risk and exchange rate risk MCs have lower leverage Chen, Cheng, He and Kim 1997 U.S. 1984 - 1993 Multiple regression analysis panel data debt ratio(long-term debt) Bankruptcy costs, growth, firm size, agency, profitability MCs have less debt ratio than DCs Akhtar - 2005 Australia 1992 - 2001 Cross-sectional Tobit regression analysis
LEVERAGE Growth, profitability size, collateral value of assets, bankruptcy costs, number of overseas subsidiaries No significant difference between MCs and DCs Mari Avarmaa et al. 2011) Baltic States(Estonia, Latvia and Lithuania) Panel data 2000 - 2008.
Panel OLS LEVERAGE Age, size, tangibility ,profitability and tax
MCs have lower leverage than DCs Jungwon Suh Sungkyunkwan et al. 2013 US Panel 1981 - 2010
Panel OLS LEVERAGE Dummy_MNC Leverage is not significantly lower for MCs Note: This table summarizes the previous empirical studies to investigate if multinational corporations have different capital structure compared to their domestic counterparts. The columns show the year of study and author, methodology, period, variables and research findings.
3. Data and Research Methodology
In this section, first, the construction of the sample is discussed. Then the dependent, independent and control variables are defined. After that, the descriptive statistics on the firm-specific and country-firm-specific variables is given. Finally, the models firm-specifications used are presented.
3.1. Sample description
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The sample period of the study covers the period from 2003 to 2014. In order to observe and examines any difference in the behaviour and leverage of the sample firms, the sample is studied during the pre-financial crisis (2003-2007) and post-financial crisis (2009-2014) periods. The division of the sample by periods is basically made to clearly observe the effects of the recent financial crisis on the capital structure and determinants of capital structure for the sample DCs and MCs. The year 2008 is left out from the univariate and regression analysis as it is the financial crisis period and might have abnormal effects on firms’ capital structure and determinants.
The sample on the study is divided into two subsets of DCs companies and MCs. These firms are distinguished between MCs or DCs based on the number of foreign subsidiaries the firm operates. A firm having foreign subsidiaries is classified as MCs. DCs are those firms with no subsidiaries outside their home country. Firms in the public utilities and financial sector are also excluded from the analysis due to their fundamentally different financial structure. The reason is that they are under various regulations that can heavily influence their capital structure decisions and hence make results difficult to interpret. In order to enhance the quality of the data, some filters are applied. To be included in the sample firms are required to have available (long-term) leverage data for the sample period and, at least, three years data for other explanatory variables. Firms reporting a negative leverage data and firms with extreme values are excluded from the sample selection. Finally, a total sample of 2,150 firms from BRICS are included in the study. An overview of the sample, broken down by country, industry, and period is given in Table A1.- A4 in the appendix.
3.2. Data
The data used in this paper is obtained from multiple sources. All Annual Data used to determine the firm-specific data for the period 2003-2014 is retrieved from Thomson Reuters DataStream. Data for the number of foreign subsidiary and age of the firm is extracted from the Orbis database. Data on country-specific variables are collected from World Development Indicators and Financial Structure Database of the World Bank.
3.3. Definition of variables and measurements
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variables and definitions used in this study is presented. Finally, table 3.1 gives the summary of the variables used.
Dependent variable
The most commonly used leverage (LEV) of capital structure is long-term debt. Some studies only analyse the total debt leverage (Deesomsak et al., 2004) while others also include long-term and short-term leverage in their analysis (Booth et al., 2001; De Jong et al., 2008 ). The short-term debt consists of commercial papers, promissory notes letters of credit and so on which makes interpretation more difficult than the long-term market leverage ratio. The book value of long-term debt over the market value of total assets is used to define the leverage ratio in this study.
Firm-specific Independent variables
These variables are explained for their importance in the literature review section. This part explain how they are defined for the research. Growth (GROW) is the variable for growth opportunity of a firm. It is measured by the market value of total assets over the book value of total assets. Tax rate (TAX) is the rate levied on the profit of a firm by all levels of government (i.e. state and country). The tax rate is measured by total income tax divided by the pre-tax income. Profitability (PROF) is the financial benefit gained from a business activity that is realized when revenue exceeds the costs and expenditures needed to sustain the business activity. The ratio of earnings before interest, taxes, depreciation and amortization (EBITDA) over the total assets is used as a measure of profitability. Assets tangibility (TANG) refers to net fixed assets (e.g. land, building, machines and equipment) ratio to total assets. It measures the capacity of firm’s assets as collateral for a debt.
Country-specific Independent variables
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market development and the bond market capitalization. The market capitalization of a bond (MARKET_CAP) is the total value of private domestic debt securities issues as a percentage of GDP. Stock market capitalization (STOCK) is the total value of listed shares as a percentage of GDP.
Control Variables
SIZE: is the control variable which is measured in most previous studies by the natural logarithm of total assets King and Santor (2008). The probability of defaults for large firms is expected to be lower than smaller ones. This is because large firms often are more diversified and have more stable cash flows than the smaller firms. Age (AGE): is the natural log of the number of years since the establishment of the company.
Table 3.1 – Summary of variables
Variable Abbreviations Definition Dependent Variable
Long-term leverage LEV Long-term debt over the market value of total assets.
Firm-specific determinants
Growth GROW Market value of total assets over book value of total assets. Tax TAX Total income tax divided by pre-tax income.
Profitability PROF EBITDA over total assets.
Asset Tangibility TAN Net fixed assets over the book value of total assets.
Country-specific determinants
Capital formation CAPITAL Annual gross capital formation as percentage of GDP (Source: World Development Indicators dataset)
Enforcement ENFORCEMENT The average of multiple governance indicators; Legal efficiency, Legal rights, Rule of law and Corruption. (Source: Worldwide Governance Indicators dataset)
GDP growth GDP Annual GDP growth rate (Source: World Development Indicators dataset)
Market capitalization of Bond MARKET_CAP Total value of private domestic debt securities issues as a percentage of GDP. (Source: Global Financial Development dataset)
Stock market capitalization STOCK Total value of listed shares as percentage of GDP. (Source: Global Financial Development dataset)
Control Variables
Firm size SIZE Natural logarithm of total assets.
Age AGE Natural logarithm of the number of years since the establishment of the company
Note: This table defines all the dependent and independent variables that are used in the models. The data needed to calculate the firm-specific variables and control variables are retrieved from DataStream and Orbis. The country-specific data for the variables are obtained from World Development Indicators dataset, Worldwide Governance Indicators dataset and Global Financial Development dataset of the world Bank.
3.4. Descriptive statistics
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Long-term leverage ratio for MCs and DCs from BRICS countries
Figure 3.1 - long-term leverage ratio for MCs and DCs for all BRICS countries.
Note: This graph shows the average long-term leverage ratio of firms categorized as multinational corporations (MCs) and Domestic corporations (DCs) from the BRICS countries over the time period 2003-2014. Source: Own calculations for the all sample firms based on data from DataStream.
Figure 3.1 shows the year to year average leverage ratio for MCs and DCs based on. It reveals that the average leverage of MCs in the sample is higher than the average of DCs over the whole sample period. On average, the leverage ratio has also increased over the study period. In comparison, the average leverage change seems to be higher for MCs compared to DCs. Another interesting observation from Figure 3.1 is that the average long-term leverage ratio increased for both MCs and DCs during the financial crisis period. Starting from 2007 until 2010 there was an overall increase of 4% for both MCs and DCs. After this period, the leverage ratio seems to stabilize but remained at higher percentage points than the pre-financial crisis period. This indicates the pre-financial crisis has caused the leverage ratio of firms to increase.
By considering the previous graph, one can not generalize MCs have higher leverage ratio than DCs for the sample period in all countries. Therefore, in order to understand the capital structure of the BRICS MCs and DCs and the dynamics over time, it is important to see the pattern on the leverage ratio of MCs and DCs separately for each country. Figures 3.2a and 3.2b depicts the year to year average long-term leverage ratio of DCs and MCs. As these figures present the leverage ratio is not similar for BRICS country comparison. Overall, Chinese firms (MCs and DCs) have the lowest leverage ratios during the whole sample period compared to the other countries. On the other hand, Indian firms (MCs and DCs) have higher leverage ratio during the pre-financial crisis period. In the post-financial crisis period, the
0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Long term leverage ratio
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average leverage ratio of Indian firms has plunged significantly and is replaced by Brazilian firms (MCs and DCs) as highly leveraged firms among the BRICS countries. These figures also show that the Brazilian, Indian and Russian MCs seem to reach similar levels of long-term leverage ratio in the post-financial crisis period.
The average long-term leverage ratio firms have increased sharply starting 2007 and remained at high levels during 2008. From these figures, it can be deduced that first the financial crisis has brought major change to the overall leverage ratios of all firms. Secondly, MCs and DCs even though they follow some patterns they are not alike in their pattern of capital formation. Lastly, this heterogeneity of leverage ratio among the countries implies the BRICS to be not similar in their institutional and financial environment.
Figure 3.2a - long-term leverage ratio for all DCs firms per country.
Note: This graph shows the average long-term leverage ratio of firms categorized as multinational corporations (MCs) per country. Source: data on sample firms based from DataStream.
0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 22% 24% 26% 28% 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Long-term leverage ratio of MCs
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Figure 3.2b - long-term leverage ratio for all DCs firms per country.
Note: This graph shows the average long-term leverage ratio of firms categorized as Domestic corporations (DCs) per country. Source: data on sample firms based from DataStream.
Table 3.2 presents the descriptive statistics of leverage and the firm-specific variables used in the regression analysis. The mean of long-term leverage is approximately 11% and a median of 5% for the all BRICS sample firms over the sample period of 2003-2014. Descriptive statistics on firm-specific variables for all countries can be seen in appendix A.5. The long-term leverage of this BRICS firms varies from country to country significantly. China has the lowest mean long-term leverage while India has the highest mean long-term leverage. The mean and median of the average growth potential of firms are about 7% and 8% respectively. This shows firms have fairly a good potential for growth. Growth opportunities signal future profitability and possibly an ability to borrow. Indian firms have a higher mean ratio of growth (GROW) compared to the average growth ratio of firms from the other countries. Firms from South Africa face relatively less growth potential with the mean average growth ratio of 3%. Brazilian firms have on an average higher tax rate of 22% which is slightly higher compared to the other countries. Overall the BRICS have a mean ratio of 19% tax. In general, all the firms have a high profitable mean ratio of 9%. The Brazilian firms leading the countries with the highest profitability mean ratio of 14%. The ratio of tangible assets indicates the level of tangible assets that can be used as collateral to secure debt. The average mean tangibility ratio is 36% of total assets with Brazilian firms having the higher tangibility ratio South African firms have lowest tangibility ratio from the group. Size and Age of the firms are similar in all the firms with Russian firms being slightly older and bigger in size. 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 22% 24% 26% 28% 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Long-term leverage ratio of DCs
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Table 3.2: Firm-specific descriptive statistics for all BRICS countries in the period 2003-2014
LEV GROW PROF TAX TANG SIZE AGE
All Countries Mean 0.1090 0.0741 0.0911 0.1919 0.3565 14.7681 2.8794 Median 0.0465 0.0837 0.0922 0.1793 0.3272 14.8192 2.7726 Maximum 2.1922 1.0000 17.0632 156.5556 2.9143 21.5733 5.7104 Minimum 0.0000 -58.6500 -50.1584 -140.1045 -0.0508 5.9402 0.0000 Std. Dev. 0.1532 0.6556 0.6034 3.5038 0.2249 1.5645 0.7416 Note: The firm-specific descriptive statistics are presented for all countries pooled for the year 2003-2014. For each country, the firm-specific descriptive statistics it is presented in the appendix table A.5.
Table 3.3 shows the firm-specific descriptive statistics between MCs and DCs. MCs in the sample have a higher leverage of 12% mean value to be compared with 10% for the DCs. On average, MCs have also higher growth and profitability ratio compared to their domestic counterparts. Moreover, DCs have on average more tangible assets than MCs.
Table 3.3: Firm-specific descriptive statistics of all MCs and DCs for the period 2003-2014
MCs DCs
Mean Med. Max. Min. Std. Dev. Mean Med. Max. Min. Std. Dev. LEV 0.1218 0.0766 1.7374 0.0000 0.1421 0.1055 0.0377 2.1922 0.0000 0.1559 GROW 0.1125 0.1087 0.9998 -5.5100 0.2763 0.0636 0.0754 1.0000 -58.6500 0.7250 TAX 0.1908 0.2106 11.8435 -24.9930 1.0620 0.1922 0.1718 156.5556 -140.1045 3.9132 PROF 0.1295 0.1161 1.4482 -2.1890 0.1269 0.0806 0.0866 17.0632 -50.1584 0.6770 TANG 0.3247 0.2889 2.9143 -0.0508 0.2206 0.3651 0.3383 1.6062 0.0000 0.2253 SIZE 15.6225 15.6841 20.2174 8.9188 1.5631 14.5355 14.6220 21.5733 5.9402 1.4820 AGE 3.1336 2.9444 5.3471 0.0000 0.8298 2.8101 2.7081 5.7104 0.0000 0.6999 Note: The firm-specific descriptive statistics are presented for all firms categorized multinational corporations (MCs) and domestic corporations (DCs) pooled for the year 2003-2014.
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post-financial crisis change in the country-specific variables, a comparison is made in appendix A.6. As it can be observed the GDP growth have reduced its pace in all countries with the most hit being Russia and South Africa. There is not much change in the enforcement side pre and post-financial crisis but a drop in this measure is observed in all countries except Brazil. The financial crisis has caused a major turbulence, in the beginning, years but in the latter years, the BRICS seem to return to the norm. From this comparison, it can be understood that the financial crisis had not had much impact on the country-specific variables. The full country-level descriptive statistics is presented in appendix A.7.
Table 3.4 - Country-level descriptive statistics
CAPITAL ENFORCEMENT GDP MARKET_CAP STOCK
All Countries Mean 0.3808 0.3674 0.0818 0.6780 0.7217 Median 0.4188 0.3577 0.0854 0.7276 0.6328 Maximum 0.4768 0.6440 0.1420 0.8025 1.7897 Minimum 0.1706 0.2500 -0.0782 0.3075 0.0860 Std. Dev. 0.1024 0.1035 0.0349 0.1249 0.4700 Note: The Country-specific descriptive statistics are presented for all countries for the year 2003-2014. For each country, the country-specific descriptive statistics is presented in the appendix A.7
3.5. Correlation matrix
Table 3.5 shows the outcomes of the correlation matrix for all major variables used in the study. As can be seen on the table, there is no strong correlation between the dependent variables and the independent firm-specific variables. And all the firm-specific explanatory variables have low correlation with each other. Growth is correlated positively with leverage., the pecking order theory proposes a positive relationship to exist between leverage and growth opportunity.
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Table 3.5 - Correlation matrix.
Correlation LEV GROW TAX PROF TANG CAPITAL
ENFORC
EMENT GDP
MARKE
T_CAP STOCK SIZE AGE
LEV 1.000 GROW -0.011 1.000 TAX -0.013 -0.001 1.000 PROF -0.018 -0.085 0.005 1.000 TANG 0.314 0.005 -0.005 0.018 1.000 CAPITAL -0.167 0.027 0.005 -0.024 0.022 1.000 ENFORCEME NT 0.141 -0.023 0.000 0.012 -0.025 -0.723 1.000 GDP -0.135 0.032 0.001 -0.012 0.048 0.672 -0.354 1.000 MARKET_CAP -0.087 0.014 0.008 -0.020 -0.027 0.597 -0.055 0.331 1.000 STOCK -0.065 0.024 -0.001 -0.003 -0.055 0.368 -0.174 0.326 0.243 1.000 SIZE 0.241 0.153 -0.011 0.073 0.145 0.085 -0.218 -0.063 -0.063 0.050 1.000 AGE 0.122 -0.009 0.001 0.039 -0.029 -0.444 0.209 -0.446 -0.350 -0.034 0.171 1.000
The table shows the firm-specific and country-specific determinants of capital structure and their correlation with the independent variable long-term leverage.
3.6. Model specification
To compare the capital structure and determinants for MCs and DCs, a multivariate analysis is done. The aim is to investigate the capital structure through firm-specific and country-specific determinants of capital for MCs and DCs. A panel data regressions analysis with leverage as the dependent variable and the explanatory variables expected to affect to affect the leverage ratios is conducted. In order to understand if the capital structure and determinants differ for MCs and DCs and if it has changed after the financial crisis, the analysis is done on the two sub-period. To take advantage of a panel data, a fixed-effect estimator is used in the equation to control for unobservable firm characteristics and year effects. The appropriateness of the fixed-effects model over the random-effects model is confirmed by the Hausman test. The model used is the classical model of Rajan and Zingales (1995) and adjusted for relevant variables for the study. The empirical model used to estimate the relationship is:
𝐿𝐸𝑉i,t = αi,t + 𝛽1GROWi,t + 𝛽2TAXi,t + 𝛽3PROFi,t + 𝛽4TANGi,t + 𝛽5SIZEi,t + 𝛽6AGEi,t + 𝜀i,t (1)
LEV is the long-term leverage ratio for the ith firm at time t. GROW, TAX, PROF and TANG are the explanatory variables for the ith firm at time t. 𝜀 is the random error term for
ith firm at time t and αi,t is the regression intercept which can vary across firms and over time. SIZE and AGE are the control variables.
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conditions and are more vulnerable to the economic and financial cyclical changes in a country. This results in the following model:
𝐿𝐸𝑉i,t = αi,t + 𝛽1GROWi,t + 𝛽2TAXi,t + 𝛽3PROFi,t + 𝛽4TANGi,t + 𝛽5CAPITALi,t +
𝛽6ENFORCEMENTi,t + 𝛽7GDPi,t + 𝛽8MARKET_CAPi,t + 𝛽9STOCKi,t +𝛽10SIZEi,t + 𝛽11AGEi,t +𝜀i,t
(2)
4. Empirical results
This section presents the empirical results of the study on the capital structure between MCs and DCs, and analyzes if there is a significant difference on the BRICS based MCs and DCs. The results are reported in three parts. In the first section, a univariate analysis concerning the difference in the mean of the long-term leverage ratio between MCs and DCs and also for the differences in the mean leverage ratio of firms’ pre and post-financial crisis period is presented. In the second part, a multivariate analysis of the firm-specific determinants of capital structure is presented. Finally, the country-specific determinants of capital structure are also added in the model and assessed to find out if they have any influence in determining the capital structure of the MCs and DC in the sample.
4.1. Univariate analysis
In the previous section, it shows that the MCs have higher leverage ratio compared to DCs. Furthermore, it also presented the average long-term leverage ratio has increased in the post-financial crisis period. In this section, a univariate analysis in the long-term ratio is conducted to test whether the leverage ratio indeed significantly differ from pre-crisis to post-crisis and between MCs and DCs. The value of the pre-post-crisis and post-post-crisis period is calculated for the years 2003-2007 and 2009-2014. The results are presented in table 4.1.
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in Brazil, India, and Russia during the pre-financial crisis period. In the post-financial crisis period, DCs seem to adjust their leverage ratio to the leverage levels of MCS. From these three countries that showed a very significant difference in the long-term leverage of MCs compared to DCs, only in Russia the significant difference continues even post-financial crisis period. On the other hand, the leverage ratio for MCs and DC in Brazil and India is not significantly different. The whole t–test tables are present in the appendix B.1 and B.2.
Table 4.1 Univariate t-test of mean differences of leverage between MCs and DCs
Pre-crisis (2003-2007) Post-crisis (2009-2014) Difference (Pre > Post) Significance (t-test) All BRICS-countries MCs 0.10 0.12 -0.02 -4.8230*** DCs 0.09 0.11 -0.02 -6.9925*** Difference (MCs > Dcs) 0.01 0.01 Significance (t-test) 3.0906*** 4.7120*** Brazil MCs 0.18 0.20 -0.02 -1.1434 DCs 0.14 0.19 -0.05 -3.8929*** Difference (MCs > Dcs)? 0.04 0.01 Significance (t-test) 2.4219** 0.6096 China MCs 0.06 0.09 -0.03 -6.0536*** DCs 0.06 0.08 -0.02 -8.4091*** Difference (MCs > DCs)? 0.00 0.01 Significant? (t-test) 0.7237 2.9546*** India MCs 0.19 0.20 -0.01 -0.5432 DCs 0.25 0.19 0.06 5.4265*** Difference (MCs > DCs)? -0.06 0.01 Significant? (t-test) -4.0805*** 0.7987 Russia MCs 0.10 0.18 -0.08 -4.0389*** DCs 0.09 0.13 -0.04 -3.7652*** Difference (MCs > DCs)? 0.01 0.05 Significant? (t-test) 0.3044 3.0659*** South Africa MCs 0.11 0.11 -0.00 -0.6014 DCs 0.12 0.12 0.00 0.6182 Difference (MCs > DCs)? -0.01 -0.01 Significant? (t-test) -1.2776 -0.1866
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4.2. Firm-specific results
To investigate the key firm-specific determinants of capital structure on long-term leverage, a fixed effects regression model is used first on MCs and DCs of the BRICS. The results of the regression models are presented in table 4.2. It has been observed BRICS have a diverse nature of the capital structure, nevertheless, these two countries seem to have similar long-term leverage ratios. To check for the consistency of the firms-specific effect on MCs and DCs same firm-specific regression analysis is conducted on the sample from Brazil and India. The results of the regression model for Brazil and India is presented in appendix B.3. Pre-financial Crisis
In this period, the significant firm-specific determinants for BRICS’ MCs and DCs are profitability, tangibility, and size. As can be observed from table 4.2 column 2. The profitability variable is positively related to leverage for MCs while it shows a negative relationship for DCs. According to Myers and Majluf (1984) of pecking order theory firms prefer to raise capital first from retained earnings, second from debt and last from issuing new equity according to, while, more profitable firms are expected to have a lower chance of bankruptcy and in turn, be able to afford to use more debt according to the trade-off theory. The negative relationship between leverage and profitability for DCs supports the pecking order theory. Tangibility is also positively related to the leverage ratio for both MCs and DCs but with varying significance and magnitude. It shows tangibility is the most important predictor for DCs than for MCs. As the theory suggests long-term leverage is expected to be positively correlated with tangible assets. This is because it serves as good collateral for a long-term debt. As tangibility increases, collateral increases, therefore, firms should be able to find more debt. The impact of size on leverage is positive for MCs but negatively related for DCs.
Post-financial Crisis
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change in the firm-specific determinants with profitability related negatively to leverage and tangibility coefficient remained positive. The change is in the variable size now becomes positive and significant similar with the results for MCs. Both MCs and DCs; having a negative and highly significant coefficient on profitability variable; suggests that firms in BRICS tend to support the pecking order theory’ of capital structure. More profitable firms naturally possess more internally generated funds, which would reduce the need for borrowing.
The regression on Brazil and India presented in table 4.4 also have shown some similar results with firm-specific regression on BRICS sample. In both countries, the variable profitability is statistically strong and negatively related while tangibility and size are positive and significant determinants of capital structure.
4.3. Country-specific results
Table 4.3 presents the long-term leverage ratio of all firms as dependent variables explained by the firm-specific and country-specific determinants for the sample period subdivided into pre-financial crisis and post-financial crisis periods.
Pre-financial Crisis
After the country-specific variables are introduced the explanatory level of the model have increased. And some firm-specific coefficients have increased in magnitude and significance. In the pre-financial crisis period, the only significant predictor variable is the capital formation of the countries for the DCs while the other variables are not significant determinants for both MCs and DCs. Even though it remained positively related to leverage ratio for both MCs and DCs it was never significant predictor for MCs while it has consistently showed significant relationship for DCs.
Post-financial Crisis
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MCs and significant. This also shows MCs have started to rely heavily in their domestic stock markets are the financial markets contracts in the other world.
Table 4.2 Panel regression results for firm-specific determinants on MCs and DCs from BRICS.
ALL BRICS Firms
Variables Pre-Financial Crisis Post-Financial Crisis Predicted Values
MCs DCs MCs DCs MCs DCs C -0.3820*** 0.1144** -0.0190 -0.4594*** (-2.9000) (2.0070) (-0.1693) (-6.6937) GROW -0.0333 -0.0036 -0.0273*** -0.0009 -/+ -/+ (-0.2950) (-0.4375) (-3.4613) (-0.2451) TAX 0.0002 0.0000 -0.0003 0.0002 + + (0.3217) (0.0176) (-0.6874) (0.6960) PROF 0.0910*** -0.0087*** -0.3144*** -0.0099*** -/+ -/+ (3.2648) (-4.5997) (-4.6895) (-2.7920) TANG 0.0428* 0.1291*** 0.0989*** 0.1320*** + + (1.8917) (9.0482) (3.4567) (9.8986) SIZE 0.0375*** -0.0079** 0.0382*** 0.0293*** -/+ -/+ (4.2257) (-2.0326) (6.9044) (9.9314) AGE -0.0366* 0.0121 -0.1460*** 0.0306 - - (-1.8715) (1.0199) (-5.4781) (1.6127) No. Observations 1665 5455 2235 7424 Adj. R2 0.7289 0.6788 0.7221 0.7350
Notes: Notes: The table shows regressions of leverage, long term debt on firm-specific variables for all BRICS MCs and DCs. The results are for the pre- and post-financial crisis period. The t-statistics are shown in parentheses underneath the coefficients. *** indicates level of significance at 1%, ** level of significance at %5, and * level of significance at 10%.
Table 4.3. Panel regression results for MCs and DCs of all BRICS’ countries.
Variables Results Predicted Values
Pre-Financial Crisis Post Financial Crisis Whole sample period
29 (0.7897) (2.4806) (0.0008) (3.5870) (1.0723) (3.8915) ENFORCEMENT 0.1906 0.1264 0.0030 -0.0061*** 0.0006 0.0010*** + + (0.5632) (0.4772) (1.4699) (-4.3187) (1.5236) (4.2393) GDP -0.1651 -0.4031 0.4284*** 0.4846*** -0.1221 -0.1206** + + (-0.3908) (-1.2772) (2.7779) (5.5161) (-0.9258) (-1.8580) MARKET_CAP 0.0189 -0.2068 0.0723 -0.0142 0.0106 -0.1451*** + + (0.4789) (-6.5026) (0.5371) (-0.1248) (0.2720) (-5.2626) STOCK -0.0044 -0.0095 -0.0438*** -0.0169 0.0124 -0.0263*** - - (-0.1976) (-0.5917) (-2.8302) (-1.5953) (1.1414) (-4.3093) SIZE 0.0237** 0.0106*** 0.03427*** 0.0326*** 0.0290*** 0.0273*** -/+ -/+ (2.5313) (2.6445) (6.0476) (11.0361) (7.7444) (6.8759) AGE -0.0216 -0.0221* -0.1804*** 0.0355* -0.0470*** -0.0258*** - - (-0.8871) (-1.7921) (-5.6320) (1.6751) (-4.1106) (-3.9781) No. Observations 1560 5352 2125 7320 3937 13771 Adj. R2 0.7564 0.7166 0.7313 0.7440 0.5795 0.6411
Notes: The table shows regressions of leverage, long term debt on firm-specific and country-specific variables for all BRICS MCs and DCs. The results are for the pre- and post-financial crisis period. The t-statistics are shown in parentheses underneath the coefficients. *** indicates level of significance at 1%, ** level of significance at %5, and * level of significance at 10%.
5. Summary and Discussion of results
This research paper tried to discuss the difference between MCs and DCs capital structure and determinants of the capital structure for the period of 2003 to 2014. First, univariate analysis compared the leverage ratio of BRICS MCs and DCs among themselves. Furthermore, the average leverage of firms is assessed to see if they have changed also over time, particularly post-financial crisis period. and their difference with time trying to identify if indeed MCs and DCs based on BRICS have a significant difference in their capital structure. The results showed that MCs to have higher leverage ratio compared to DCs. The results also explained that the financial structure of firms changed after the financial crisis. Firms have in general higher leverage ratio in the post-financial crisis compared to pre-financial crisis period.
Second, to provide an explanation and understand the determinants of the capital structure of the BRICS firms, a regression analysis on the firm-specific and country-specific determinants is conducted.
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as they can finance their investments quite smoothly. MCs are significantly influenced by profitability as it appears to be the most important firm-specific determinant of capital structure. Particularly after the financial crisis. Tangibility is the most important firm-specific determinant of capital structure for DCs, while it has positive relations on leverage, it is far less in important before the financial crisis, However after the financial crisis, it has become so much important for MCs as well.
6. Conclusion
This study presents the capital structure and the firm-specific and country-specific determinants of capital structure on a sample of BRICS countries multinational MCs and domestic corporations over the period of 2003-2014. The results presented in this paper suggest that the capital structure of MCs from emerging economies are statistically on average higher than the DCs. However, analysing pre and post financial crisis in between countries reviled that the average long-term leverage is not significantly different for MCs and DCs compared, except in Russia. Overall, the BRICS firms have a divergent capital structure among the countries which makes the comparison in between MCs and DCs firms difficult. However, observing the pre and post financial crisis period also helped to get a better picture in the dynamics of the long-term leverage and determinants of firms from emerging economies.
The financial crisis had a major impact on the financial markets, greatly reducing security issuance by firms and lending by financial institutions. One of the consequences of the disruption of the capital and lending markets caused by the financial crisis was to significantly increase the amount of debt in firm capital structures. The global financial crisis have led to many economic hardships, it has also paved a way to examine the role of firm-specific factors in capital structure decisions when firms are financially constrained, due to the financial crisis they tend to focus more on internal finance.
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Although the paper is having a sample of firms from variously industries not studding the impact of their difference in terms of industry is limitation of the paper. Further studies can also expand the research if the financial crisis had similar or same effected across all industries. Other measures for multinational corporations were considered but data was not available for most of the firms in the sample. It would give more value to the study to substantiate the results of the study with several measures of for multinational corporation.
As a recommendation for management should think ways to internationalize their firms at least to countries with better institutional system that is expected to help firms relieve their fixed stock and raise finance more easily. This can give firms easily access to both the domestic and the international financial markets. This advantage is particularly observed pre financial crisis period for MCs from BRICS having not big coefficient of tangibility to leverage but this has changed with the financial crisis impacting even the better suited countries. However, for short run management should use short-term debt is gives more flexibility and is better suited in matching for the unexpected changes of financial needs particularly for the periods of financial crisis. In addition profitability has been a significant determinant of capital structure for MCs and DCs therefore directors of companies in BICS should pay more attention to remain profitable until long term financing constraint is solved.
As government policy makers they should observe the huge potential of growth of the firms in the BRICS countries and financial constraints particularly to domestic corporations the countries need to develop their institutional capacity and improve the bankruptcy and creditors right and governance and lift firms from the pressure of lenders requiring stock fixed assets to be used for collateral. With bigger growth opportunity and profitability available in BRICS countries they should also work to create an atmosphere of good investment for FDI inflows. There should also be policies intended to encourage DCs to gain access to the capital market as this moment only MCs seem to be more using the capital markets.
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Acknowledgments
I would like to give my utmost thank to Dr. Hein Vrolijk for his insightful comments, supervision and swift feedbacks while writing this thesis. I also want to thank all friends and family who gave me valuable support during my study.
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