The effect of multinationality on
the firm’s leverage ratio;
international evidence
Master Thesis
MSc International Financial Management
Bas Bleeker
s2298201University of Groningen Faculty of Economics & Business
Supervisor: A. De Ridder
Co-Assessor: dr. R.O.S. Zaal
Abstract
International business studies have long been interested in investigating the determinants of a firm’s optimal capital structure. This study presents empirical evidence regarding the implications of the agency theory. The theory assumes that MNCs will rely more on equity to overcome the agency costs of debt. The findings are based on a sample of 10 countries and 4325 firm-year observations measured over a 5-year period and indicate that the level of multinationality has a significant negative effect on the firm’s leverage ratio. Moreover, the moderating effect of a country’s formal institutions and legal origin significantly influence this relationship.
Contents
1. Introduction ... 4
2. Literature review ... 7
2.1 Multinationality effects on firm leverage ... 7
2.2 Formal institutions ... 9
2.3 Legal origin ... 11
3. Data, variables and research method ... 12
3.1 Definition of formal institutions ... 13
3.2 Definition of key variables ... 14
3.3 Multivariate analysis ... 22
4. Results ... 23
4.1 Leverage regressions ... 25
4.2 Results of a country’s formal institutions and legal origin ... 27
5. Conclusion ... 30
6. Further research ... 31
References ... 32
1. Introduction
Over the last decades more and more firms have entered foreign markets in order to respond to the new external demands in the rapidly changing global environment. International studies show several reasons why a firm’s level of multinationality is important in the global economy. First, by having multiple foreign operations in a wide range of countries, Multinational Corporations (MNCs) are exposed to a variety of economic systems and conditions. These differences may be reflected in the level of a country’s formal institutions (Bartlett, 2003). Moreover, one of the benefits of MNCs is their wider access to international capital markets and thus their ability to diversify their funding sources (Park et al., 2013). According to Jang (2017, p. 4133): “Expanding operations overseas can improve access to capital markets and lower the cost of capital.” Burgman (1996) mention the traditional view of a trade-off between the debt tax shelter and expected bankruptcy costs, where MNCs are expected to have higher leverage ratios and lower expected bankruptcy costs. In fact, the literature does not find a conclusive answer whether MNCs have lower or higher leverage ratios compared to pure domestic firms.
expense of the shareholders. While the level of multinationality could affect a firm’s leverage ratio, the overall effect of an increase in multinationality on the firm’s leverage ratio is still questionable due to different empirical explanations. Moreover, the moderating effects of a country’s formal institutions and a country’s legal origin might influence the strength of this relationship. Since the work of La Porta et al. (1997; 1998; 2002), an increasing stream of law and finance literature has shown that institutions might affect corporate decision-making (Claessens et al., 2001). Especially interesting in this research is how these differences in institutional features like the level of formal institutions and a country’s legal origin could moderate capital structure choices of MNCs in developed countries. Rajan and Zingales (1995) focused their sample on the G-7 countries. However, this research starts by presenting the capital structure of the MNCs in 10 European developed countries (United Kingdom, the Netherlands, Belgium, France, Germany, Switzerland, Denmark, Sweden, Finland and Norway). This results in a unique sample of detailed measures and comparable analyses of a firm’s leverage ratio. Moreover, this sample covers the three legal origins of a country’s law, in which the major institutional differences across countries can be analysed and their likely impact on a firm’s capital structure. Park et al. (2013) suggest that the level of a MNCs leverage ratio does not significantly differ compared to their domestic counterpart by controlling for key firm characteristics associated with asset intangibility. However, this study is the first that is intended to examine the country level moderating effects of a country’s formal institutions and legal origin on the relationship between the level of multinationality and the firm’s leverage ratio.
findings are an important source for directing the internationalisation of multinational enterprises. Concisely, the research question used in this paper will be the following:
What is the moderating effect of changes in a country’s formal institutions and legal origin on the relationship between the level of multinationality and the firm’s leverage ratio?
The purpose of this study will be to evaluate the way in which the level of multinationality affect the capital structures of MNCs. Moreover, this study examines whether there are any additional international factors and firm specific factors that may help explain the financing policies of MNCs. This will be done through an empirical examination that consists of two parts. The main relationship examines whether the level of multinationality affects a firm’s leverage ratio, whereas the second part of this study will elaborate on the difference in a firm’s leverage ratio, taking into account the formal institutions of a specific country and a country’s legal origin. Using a sample of 4325 firm-year observations representing 865 unique firms from 10 countries over a research period from January 2010 until December 2014, I find significant evidence for a negative relationship between the level of foreign involvement and the firm’s leverage ratio. Similar to evidence of Doukas and Pantzalis (2003), I find support that MNCs are subject to higher agency costs as their level of multinationality increases. Following the agency costs perspective, MNCs will rely more on equity to overcome the agency costs of debt and thus have lower leverage ratios compared to their domestic counterpart. Moreover, I found in all tested models significant evidence for the existence of the moderating effect of a country’s formal institutions. In some of the tested models there was enough evidence to support the moderating effect of a country’s legal origin. However, in all of the tested models the main relationship between the level of multinationality and a firm’s leverage ratio remains highly significant.
2. Literature review
Various scholars have noticed the increasing attention of multinationality on the firm’s leverage ratio. Over the last decades, more and more firms have gone abroad by entering foreign markets characterized by different financing policies of MNCs compared to their domestic counterpart. Moreover, MNCs face different strengths of formal institutions in the foreign country where they are operating, which can be considered as an important determinant of firm outcomes (North, 1990). Following La Porta et al. (1997) the legal environment matters for the size and extent of a firm’s capital structure in a specific country and thus needs to be considered by analyzing MNCs capital options. Many studies have argued that MNCs have lower leverage compared to domestic firms, because of specific international factors such as exchange rate risk, political risk and the higher agency costs that MNC’s face, which will be explained in section 2.1 (Burgman, 1996; Lee and Kwok, 1988; Mansi and Reeb, 2002). However, none of these studies controlled for the effects of a firm’s growth potential, profitability and asset tangibility. Doukas and Pantzalis (2003) were the first that controlled for these intangible firm specific characteristics. Following Doukas and Pantzalis (2003), the results show that the negative effects of the agency costs of debt, specifically on long-term leverage, are significantly greater for firms with increasing foreign involvement. Moreover, Park et al. (2013) found that MNCs do not appear to have lower leverage compared to domestic firms by controlling for the firm characteristics just mentioned. Most importantly, literature is still questionable and showing contradictory results in whether the level of multinationality has either a positive or negative effect on the firm’s leverage ratio. The theories that explain the different effects of multinationality on the firm’s leverage ratio are presented in the following section.
2.1 Multinationality effects on firm leverage
According to Park et al. (2013) the underinvestment problem, where firms with high investment opportunities avoid the use of debt for fear of preceding investment opportunities, applies mostly to small and growth firms. Large MNCs own sufficient internal resources and thus have little reason to avoid the use of debt as a financing policy. To confirm this reasoning, Hovakimian et al. (2004) report that the tendency to issue debt increases with the size of a firm. This argues for a positive relationship between the level of multinationality and the leverage ratio of a firm. Moreover, Doukas and Pantzalis (2003, p. 61) mention: “since the operations of MNCs are geographically and industrially diversified, the financial and business risk of MNCs is expected to be lower compared to that of domestic firms.” This would enable MNCs to achieve stable cash flows and reduce the cost of debt, which consequently raises the leverage ratio of MNCs.
bonds (Kisgen, 2009). Overall, this shows the impact of the increased credit ratings stringency on the MNCs’ capital structure choices by shifting to lower leverage ratios in order to reach the minimum target credit ratings.
Moreover, the results of Doukas and Pantzalis (2003) report that the agency costs of debt are significant and positively related to the firm’s level of multinationality. This is consistent with the theory that MNCs are subject to higher agency costs than their domestic counterpart, due to the fact that geographical diversity increases information assymetries, which makes active monitoring more expensive and difficult to control. Doukas et al. (2000) confirms this view by reporting that monitoring effectiveness decreases significantly with geographical diversification. Besides, Burgman (1996) takes into account the factor exchange rate risk that may affect the leverage ratios of MNCs. Exchange rate changes can trigger financial distress that may be difficult to diversify away and thus pose substantial risk to MNCs, which could consequently lead to lower levels of debt. Lastly, Rego (2003) reports that the effective tax rate for MNCs is significantly lower than their domestic counterpart. This suggests that firms with more foreign involvement have the ability to transfer earnings from high-tax countries to low-tax countries. This could be explained by the classic trade-off theory, which states that the effect of the tax-shield of debt is an important indicator in determining a firm’s optimal capital structure. Following this theory, firms with a lower tax burden will have lower leverage ratios (Modigliani and Miller, 1963). The trade-off theory will be explained in more detail in section 3.2 of this paper. The fact that the literature is contradictory and in line with the above argumentation, the following is hypothesized:
Hypothesis 1a: The higher level of multinationality has a positive effect on the firm’s leverage ratio
Hypothesis 1b: The higher level of multinationality has a negative effect on the firm’s leverage ratio
2.2 Formal institutions
addresses in general terms that defined rules are set in response to the demand of the society for both the protection and benefits of the public. A defined set of rules and the enforcement of these rules constrain egocentric behavior of individuals and enforce specific behavior by punishment. According to Hantke-Domas (2003), strong formal institutions seek the benefit and protection of the public at large through the establishment of a stable formal society that maximizes the social welfare. Furthermore, strong formal institutions improve the optimal allocation of resources between people and society in a global context.
Boubakri et al., (2013) mention that stronger formal institutions are associated with lower cost of debt, which implies higher leverage ratios (Qi, Roth and Wald, 2010). La Porta et al. (1998) states that more efficient institutions and stronger investor protection are correlated with better economic and financial outcomes. Qian and Strahan (2007) confirmed this argument, by reasoning that stronger creditor rights expand the availability of loans, because the presence of better formal institutions in times of bankruptcy and reorganizations, lenders are more willing to provide credit on favorable terms afterwards. Thus, in case of strong formal institutions where creditor protection is strong, bank loans tend to have longer maturities, which result in lower interest rates and higher leverage ratios among MNCs. Moreover, in countries with weak formal institutions, where creditor rights are weak, loan ownership becomes more devious and increases the ex post cost of reorganization, which reduces the incentive for lenders to default (Qian and Strahan, 2007).
Hypothesis 2a: The effect of multinationality on the firm’s leverage ratio is stronger for companies based in countries with strong formal institutions
Hypothesis 2b: The effect of multinationality on the firm’s leverage ratio is weaker for companies based in countries with strong formal institutions
2.3 Legal origin
Previous literature highlights the importance of cross-country differences in determining firm financing choices. Rajan and Zingales (1996) found that next to firm-specific factors, country characteristics should also be considered as important determinants of corporate capital structures. La Porta et al. (1997) mention that differences in the effectiveness of financial systems, and as a consequence in the level of financial development can be explained to a country’s legal origin. Claessens et al., (2001) confirm that corporate finance choices are a reflection of institutional environments, including a country’s legal origin and protection provided to external investors and equity holders. Legal origin can be seen as the historical roots of the country’s laws on which the rules of investor protection are based (Turk Ariss, 2016). Typically, we consider civil, common and Scandinavian law. The legal rules among these countries vary systematically by legal origin. According to La Porta et al. (1997, p. 1131): “English law is common law, made by judges and subsequently incorporated into legislature. German, Scandinavian and French laws, in contrast, are legislator-made civil law tradition.”
compared to common law countries. As a result, common law countries provide MNCs with better access to equity finance than civil law countries, which means less reliance on debt and thus this could make the relationship between the level of multinationality and the firm’s leverage ratio weaker. On the other hand, MNC’s based in civil law countries will face lower levels of investor protection and consequently this might result in more reliance on debt, which strengthen the relationship between multinationality and the firm’s leverage ratio. In line with the above argumentation the following is hypothesized and included together with the aforementioned relationships in Figure 1.
Hypothesis 3: The effect of multinationality on the firm’s leverage ratio is stronger for companies based in civil law countries.
Figure 1: Conceptual model
3. Data, variables and research method
3.1 Definition of formal institutions
To quantify the formal institutions (FI) construct, I made use of the six Worldwide Governance Indicators (WGI). In a previous study of Aart Kraay and Massimo Mastruzzi, members of the World Bank, and Daniel Kaufmann, member of the Natural Resource Governance Institute (NRGI), these WGI were used as an index for a country’s level of institutional development. Based on the study of Kaufmann et al., (2007), I use the six indicators that are measured over a time-span ranging from 1996-2006 as a proxy for the variable formal institutions. The WGI are constructed by hundreds of underlying variables taken from a wide range of different data sources. The index ranges from -2,5 to 2.5, where a higher value indicates a stronger formal institutions level. The data is based on the governance views of respondents from a survey, which are experts in private, public and NGO firms and is obtained from the website: info.worldbank.org (2017). Table 1 gives a description of the six Worldwide Governance Indicators defined by Kaufmann et al., (2010).
Table 1: Description of the six Worldwide Governance Indicator (WGI)
WGI Description of indicator
1. Voice and Accountability
Captures perceptions of the extent to which country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media.
2. Political Stability and Absence of Violence
Captures perceptions of the likelihood of political instability and/or politically-motivated violence including terrorism.
3. Government Effectiveness
Captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies.
4. Regulatory Quality Captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development.
5. Rule of Law Captures perceptions of the extent to which agents have confidence in and abide by the rules of society. In particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence.
6. Control of Corruption
3.2 Definition of key variables
Previous studies have used different ways to construct the multinationality variable. The most common measure to operationalize this variable is the foreign sales ratio (Qian and Wang, 1999; Rugman and Oh, 2010; Park et al., 2013). Since the multinationality variable holds a variety of elements it could be argued, according to Sullivan (1994), that this variable can be seen as a multidimensional construct. In this study the degree of a firm’s multinationality is measured by their foreign sales ratio, which is defined as followed:
Multinationality, MNY, is calculated as
𝑀𝑀𝑀𝑀𝑀𝑀 = 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓𝑠𝑠𝑡𝑡𝑓𝑓𝑡𝑡𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓𝑠𝑠 ∗ 100% (1)
Following the study of Aabo et al. (2015), I also constructed an extra dummy variable (MNY_D) as a multinationality indicator that takes the value of one if a firm’s foreign sales ratio is greater than 30% and zero otherwise. The 30% threshold of foreign sales for the operationalization of multinationality is taken into consideration to ensure that firms classified as multinational corporations are truly firms with significant levels of foreign involvement.
Regarding the definition of a firm’s leverage ratio, previous studies did not explicitly control for intangible firm characteristics such as asset tangibility, profitability and market-to-book (Burgman, 1996; Lee and Kwok, 1998; Mansi and Reeb, 2002). Whereas Park et al. (2013) considered both the book and market leverage, these studies just focused on the market leverage. However, Graham and Harvey (2001) report that managers make critical decisions based on internal ratios of capital structures. Moreover, Park et al. (2013) mention that there is no best practice for the usage of the leverage ratio. For this reason, and in line with Jang (2017), I consider the book leverage as the leading construct for a firm’s leverage ratio, which is defined as followed:
Leverage, LEV, is calculated as
𝐿𝐿𝐿𝐿𝐿𝐿 =𝑠𝑠𝑓𝑓𝑓𝑓𝑓𝑓 𝑡𝑡𝑓𝑓𝑓𝑓𝑡𝑡 𝑑𝑑𝑓𝑓𝑑𝑑𝑡𝑡 + 𝑑𝑑𝑓𝑓𝑑𝑑𝑡𝑡 𝑓𝑓𝑓𝑓 𝑐𝑐𝑐𝑐𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑡𝑡 𝑠𝑠𝑓𝑓𝑠𝑠𝑑𝑑𝑓𝑓𝑠𝑠𝑓𝑓𝑡𝑡𝑓𝑓𝑓𝑓𝑠𝑠𝑡𝑡𝑓𝑓𝑡𝑡𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓𝑡𝑡𝑠𝑠 (2)
MNCs have relatively low leverage due to the fact that firm characterized by intangible assets are associated with a firm’s growth potential, low asset tangibility and profitability (Park et al., 2013). First, according to the pecking order theory (Myers, 2003) can profitability be associated with low leverage ratios since profitable firms enjoy sufficient internal resources and thus avoid the attraction of debt (Park et al., 2013). Moreover, Bodnar and Weintrop (1997) report that high growth potential of firms could result in relatively high valuations of MNCs equities where thus the leverage ratios of these MNCs will be low. Last, in case of low asset tangibility a relatively small amount of a firm’s total assets could be assigned as collaterals, which thus results in a low leverage ratio of a MNC. Since the OLI theory states that MNCs hold valuable intangible assets, where the presence of the intangible asset characteristics are empirically associated with lower leverage ratios (Lemmon et al., 2008; Myers, 2003; Rajan and Zingales, 1995), this study controls for intangible asset indicators like profitability, low asset tangibility and high growth potential (Lemmon et al., 2008; Myers, 2003; Rajan and Zingales, 1995).
To construct the variable legal origin I made use of two dummy variables that identifies the legal origin of the commercial code or company law from each country. The three origins in this study are: civil, common and Scandinavian law. The legal origin dummy (LO_D) is equal to one if the legal origin is civil law, and zero in case of common law. Besides, the Scandinavian law dummy (SCAN_D) equals one if the legal origin is Scandinavian law and zero otherwise. The data for these dummy variables is gathered from the study of La Porta et al. (1999).
Market-to-book ratio (MB): following Brugman (1996) MB is considered as a proxy for growth opportunities, which is defined as followed:
Market-to-book ratio, MB, is calculated as
𝑀𝑀𝑀𝑀 =(𝑡𝑡𝑓𝑓𝑡𝑡𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓𝑡𝑡𝑠𝑠 − 𝑑𝑑𝑓𝑓𝑓𝑓𝑏𝑏 𝑓𝑓𝑒𝑒𝑐𝑐𝑓𝑓𝑡𝑡𝑒𝑒 + 𝑡𝑡𝑠𝑠𝑓𝑓𝑏𝑏𝑓𝑓𝑡𝑡 𝑣𝑣𝑠𝑠𝑠𝑠𝑐𝑐𝑓𝑓 𝑓𝑓𝑓𝑓 𝑓𝑓𝑒𝑒𝑐𝑐𝑓𝑓𝑡𝑡𝑒𝑒)𝑡𝑡𝑓𝑓𝑡𝑡𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓𝑡𝑡𝑠𝑠 (3)
High growth opportunities and thus a high MB is expected to result in lower leverage ratios. Myers (1977) argues that higher levels of debt can result in underinvestment problems among high growth firms, since managers seeking to increase stockholders wealth may neglect positive NPV projects. Moreover, Baker and Wurgler (2002) found in their study that firms with a high MB have lower leverage ratios, since these firms are more incentivized to issue more equity for a higher stock price.
Profitability (PROF): measured by the earnings before interest taxes depreciation and amortization (EBITDA) and calculated as followed:
Profitability, PROF, is calculated as
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 =𝑡𝑡𝑓𝑓𝑡𝑡𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓𝑡𝑡𝑠𝑠𝐿𝐿𝑀𝑀𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 (4)
According to the trade-off theory face profitable firms lower expected costs of financial distress and these firms value the interest tax shields more than less profitable firms. Following this tax and bankruptcy costs perspective, it is expected that profitable firms have higher leverage ratios (Frank and Goyal, 2009). However, according to Chung and Wang (2018, p. 3): “empirical findings suggest a negative relationship between profitability and leverage.” For example, firms may retain low leverage ratios from a strategic point to avert their competitors’ market entry (Flannery and Rangan, 2006; Kayhan and Titman, 2007). This explanation relies on the assumption that profitability implies market dominance.
Research and development (RD): measured by the Research & Development (R&D) expenses and calculated as followed:
Research and development, RD, is calculated as
Following the trade-off theory a negative relationship is expected between RD and the leverage ratio, since a higher RD may lead to higher debt-related agency costs and higher distress costs (Chung and Wang, 2018).
Research and development dummy (RD_D): a dummy variable equal to one if the firm has R&D expenses, and zero otherwise. Since many firms do not report R&D expenses in their financial reports, I included this dummy variable to control for any possible R&D effects.
Selling expenses (SE): measured by the selling expenses and calculated as followed: Selling expenses, SE, is calculated as
𝑆𝑆𝐿𝐿 =𝑠𝑠𝑓𝑓𝑠𝑠𝑠𝑠𝑓𝑓𝑓𝑓𝑓𝑓 𝑓𝑓𝑒𝑒𝑒𝑒𝑓𝑓𝑓𝑓𝑠𝑠𝑓𝑓𝑠𝑠𝑡𝑡𝑓𝑓𝑡𝑡𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓𝑠𝑠 (6)
The trade-off theory implies a negative relationship between SE and the leverage ratio, since SE can be considered as distress costs (Chung and Wang, 2018)
Selling expenses dummy (SE_D): a dummy variable equal to one if the firm has selling expenses, and zero otherwise. Since many firms do not report selling expenses in their financial reports, I included this dummy variable to control for any possible effects of this variable.
Property, plant and equipment (PPE): measured by the net property, plant and equipment and calculated as followed:/Total Assets.
Property, plant and equipment, PPE, is calculated as 𝑃𝑃𝑃𝑃𝐿𝐿 =𝑓𝑓𝑓𝑓𝑡𝑡 𝑒𝑒𝑓𝑓𝑓𝑓𝑒𝑒𝑓𝑓𝑓𝑓𝑡𝑡𝑒𝑒 𝑒𝑒𝑠𝑠𝑠𝑠𝑓𝑓𝑡𝑡 𝑓𝑓𝑒𝑒𝑐𝑐𝑓𝑓𝑒𝑒𝑡𝑡𝑓𝑓𝑓𝑓𝑡𝑡
𝑡𝑡𝑓𝑓𝑡𝑡𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓𝑡𝑡𝑠𝑠 (7)
Firm Size (SIZE): measured by the firm’s total sales and calculated as followed: Firm size, SIZE, is calculated as
𝑆𝑆𝐸𝐸𝑆𝑆𝐿𝐿 = log (𝑡𝑡𝑓𝑓𝑡𝑡𝑠𝑠𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓𝑠𝑠) (8)
Chung and Wang (2018) mention that larger firms face lower risks due to greater diversification. Again here the trade-off theory expects a positive relationship between firm size and the leverage ratio, since diversified firms could have higher leverage ratios due to reduced operating risks.
Traditional analysis, such as Frank and Goyal (2009) and Lemmon et al., (2008), has focused on firm characteristics as the determinants for corporate leverage. However, according to Gungoraydinoglu and Öztekin (2011) countries differ in the quality of institutions that may influence the costs and benefits of a firm’s corporate capital structure. To control for these influences, this study made use of a variety of country level control variables that are based on the work of La Porta et al. (1998) and together with their definitions explained below.
Creditor rights (CRED): measured by an index (La Porta et al., 1998) ranging from 0 (weak creditor rights) to 4 (strong creditor rights). According to the trade-off theory lower leverage ratios should incur weaker creditor rights and poorer quality of the enforcement, since higher bankruptcy and agency costs of debt would be expected (Gungoraydinoglu and Öztekin, 2011).
Legal reserve requirements (RESV): measured by the minimum percentage of the total share of capital mandated by corporate law to avoid the dissolution of a firm (La Porta et al., 1998). Following the trade-off theory, lower reserve requirements will be expected with low leverage ratios, since this requirement forces firms to hold a certain level of capital in the firm to prevent liquidation and thus protects creditors (La Porta et al., 1998). Without these reserve requirements, creditors might be less willing to invest their money due to higher distress costs, which thus affects the leverage ratios of firms negatively.
shareholder rights have lower leverage ratios, since these firms are more incentivized to issue more equity (Gungoraydinoglu and Öztekin, 2011).
Industry (Industry_D): To consider the industry effect, I also include the industry dummy variable, measured by the 12 Fama-French industry classifications.
Table 2 provides the descriptive statistics for all the variables used in this study and the Appendix displays the firm-year observations per country as well as the country averages of all our variables. The average leverage ratio in this sample is 50%. This implies that on average the total debt is half of a firm’s total assets, with a minimum of 14.3% and a maximum of 91.2%. The average level of multinationality in terms of foreign sales is 60.5% and 82.2% of the firms have a foreign sales ratio of 30% or more. The formal institutions in this sample are on average ranked as 1.50 on the WGI index, with a minimum of 1.13 and a maximum of 1.87 as the strongest institution. The legal origin dummy indicates that 81.0% of the firms in this sample are based in civil law countries and thus 19.0% of the firms are legislated according to common law. Moreover, 23.1% of the firms are based in Scandinavian law countries. Finally, the firms in this sample exhibit a great variability in profitability ranging from -19.5% to 36.6%.
This table reports the descriptive statistics of all the variables used in this study. The following variables are used: leverage (LEV), multinationality (MNY), the multinationality dummy that takes the value of one if a firm’s foreign sales ratio is greater than 30% and zero otherwise (MNY_D), formal institutions (FI), the Scandinavian law dummy that equals to one if the legal origin is Scandinavian law and zero otherwise (SCAN_D), the legal origin dummy that takes the value of one if the legal origin is civil law and zero in case of common law (LO_D), market-to-book ratio (MB), profitability (PROF), R&D expenses (RD), the R&D dummy variable that equals one if the firm has R&D expenses and zero otherwise(RD_D), selling expenses (SE), the selling expenses dummy variable that equals one if the firm has selling expenses and zero otherwise(SE_D), property plant and equipment (PPE), firm size (SIZE), creditor rights (CRED), legal reserve requirements (RESV), shareholder rights (ANTD). The firm-year observations are measured over a sample period that runs from January 2010 to December 2014.
N Mean Median Std. dev. Min Max
LEV 4325 0.500 0.499 0.158 0.143 0.912 MNY 4325 60.480 63.790 28.509 2.370 100.000 MNY_D 4325 0.822 1.000 0.383 0.000 1.000 FI 4325 1.501 1.462 0.232 1.132 1.873 SCAN_D 4325 0.231 0.000 0.422 0.000 1.000 LO_D 4325 0.809 1.000 0.393 0.000 1.000 MB 4325 1.966 1.470 1.720 -0.530 11.010 PROF 4325 0.112 0.110 0.079 -0.195 0.366 RD 4325 0.019 0.000 0.038 0.000 0.197 RD_D 4325 0.465 0.000 0.499 0.000 1.000 SE 4325 0.169 0.137 0.169 0.000 0.690 SE_D 4325 0.688 1.000 0.463 0.000 1.000 PPE 4325 0.245 0.208 0.185 0.010 0.832 SIZE 4325 14.043 13.968 1.855 10.406 18.421 CRED 4325 1.972 2.000 1.436 0.000 4.000 RESV 4325 0.124 0.100 0.136 0.000 0.500 ANTD 4325 2.800 3.000 1.403 0.000 5.000
This table provides the correlation coefficients of all the variables used in this study. The following variables are used: leverage (LEV), multinationality (MNY), the multinationality dummy that takes the value of one if a firm’s foreign sales ratio is greater than 30% and zero otherwise (MNY_D), formal institutions (FI), the Scandinavian law dummy that equals to one if the legal origin is Scandinavian law and zero otherwise (SCAN_D), the legal origin dummy that takes the value of one if the legal origin is civil law and zero in case of common law (LO_D), market-to-book ratio (MB), profitability (PROF), R&D expenses (RD), the R&D dummy variable that equals one if the firm has R&D expenses and zero otherwise (RD_D), selling expenses (SE), the selling expenses dummy variable that equals one if the firm has selling expenses and zero otherwise(SE_D), property plant and equipment (PPE), firm size (SIZE), creditor rights (CRED), legal reserve requirements (RESV), shareholder rights (ANTD). The sample period runs from January 2010 to December 2014. *, **, and *** Denote significance at the 10%, 5% and 1% levels, respectively.
LEV MNY MNY_D FI SCAN_D LO_D MB PROF RD RD_D SE SE_D PPE SIZE CRED RESV ANTD
LEV 1 MNY -0.136*** 1 MNY_D -0.0924*** 0.742*** 1 FI -0.0378* 0.192*** 0.0916*** 1 SCAN_D 0.0585*** 0.104*** 0.0566*** 0.707*** 1 LO_D 0.0437** 0.0428** 0.0841*** 0.205*** 0.266*** 1 MB 0.0878*** 0.0638*** 0.00382 0.104*** 0.00499 -0.178*** 1 PROF -0.218*** 0.0122 -0.00314 0.0189 -0.0154 -0.110*** 0.325*** 1 RD -0.204*** 0.230*** 0.144*** 0.0544*** -0.0420** 0.0895*** 0.131*** 0.0276 1 RD_D -0.196*** 0.308*** 0.214*** 0.131*** -0.0272 0.0630*** 0.0596*** 0.0681*** 0.528*** 1 SE -0.156*** 0.119*** 0.0959*** 0.148*** -0.0688*** 0.00646 0.142*** 0.0142 0.409*** 0.219*** 1 SE_D -0.0691*** 0.199*** 0.154*** 0.248*** -0.00339 -0.00954 0.0982*** 0.0560*** 0.219*** 0.283*** 0.672*** 1 PPE -0.113*** 0.0244 0.000841 0.0851*** 0.0721*** -0.0675*** -0.0993*** 0.110*** -0.180*** -0.0671*** -0.106*** 0.0514*** 1 SIZE 0.164*** 0.205*** 0.153*** 0.0154 -0.0281 0.0817*** 0.138*** 0.0995*** -0.00417 0.156*** -0.0441** 0.145*** 0.0373* 1 CRED -0.0647*** 0.0310* -0.0225 0.206*** -0.0333* -0.686*** 0.165*** 0.126*** 0.0199 0.0584*** 0.175*** 0.282*** 0.123*** -0.0603*** 1 RESV -0.129*** 0.160*** 0.103*** 0.399*** 0.119*** 0.442*** 0.0111 -0.0125 0.121*** 0.0945*** 0.124*** 0.136*** 0.0118 0.0379* -0.312*** 1 ANTD 0.0177 -0.0548*** -0.0802*** -0.126*** 0.0958*** -0.761*** 0.110*** 0.0441** -0.176*** -0.161*** -0.145*** -0.171*** 0.0543*** -0.0749*** 0.229*** -0.339*** 1
The distribution of all the MNCs across the twelve Fama-French industries is presented in Table 4. This table reports that 70% of the MNCs are concentrated in the following four industries: Consumer non-durables, Manufacturing, Business equipment and Other industries.
This table reports the number of firm-year observations over a sample period ranging from January 2010 to December 2014. The classification is based on the 12 Fama-French’s industries, where Utilities and Finance firms are excluded in this sample.
Industry code Industry name Frequency Percent
1 Consumer non-durables 535 12.37
2 Consumer durables 180 4.16
3 Manufacturing 1030 23.82
4 Oil, gas, and coal extraction and products 145 3.35
5 Chemicals and allied products 205 4.74
6 Business equipment 650 15.03
7 Telephone and television transmission 100 2.31
9 Wholesale, retail, and some services; laundries, repair shops 375 8.67
10 Healthcare, medical equipment, and drugs 255 5.90
12 Other industries 850 19.65
Total 4325 100.00
N 4325
3.3 Multivariate analysis
A cross-country ordinary least square (OLS) regression analysis is used to examine the effect of multinationality on the firm’s leverage ratio. Furthermore, interaction terms are used to examine the moderating effects of the country’s formal institutions and legal origin on the main relationship between multinationality and the firm’s leverage ratio. A positive coefficient of the interaction term implies a steeper slope between multinationality and the firm’s leverage ratio if the value of the moderator is positively high. However, a negative coefficient implies a flatter slope between multinationality and the firm’s leverage ratio if the value of the moderator is negatively high. As mentioned before the results are controlled for several country and firm control variables.
The following OLS regression is used to test the main relationship between multinationality and the firm’s leverage ratio:
𝐿𝐿𝐿𝐿𝐿𝐿𝑖𝑖𝑖𝑖𝑖𝑖 = 𝛼𝛼 + 𝛽𝛽1𝑖𝑖𝑖𝑖𝑀𝑀𝑀𝑀𝑀𝑀 + 𝛽𝛽2𝑖𝑖𝑖𝑖𝑀𝑀𝑀𝑀𝑀𝑀_𝐸𝐸 + 𝛽𝛽3𝑖𝑖𝑖𝑖𝑀𝑀𝑀𝑀 + 𝛽𝛽4𝑖𝑖𝑖𝑖𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 + 𝛽𝛽5𝑖𝑖𝑖𝑖𝑃𝑃𝐸𝐸
+ 𝛽𝛽6𝑖𝑖𝑖𝑖𝑃𝑃𝐸𝐸_𝐸𝐸 + 𝛽𝛽7𝑖𝑖𝑖𝑖𝑆𝑆𝐿𝐿 + 𝛽𝛽8𝑖𝑖𝑖𝑖𝑆𝑆𝐿𝐿_𝐸𝐸 + 𝛽𝛽9𝑖𝑖𝑖𝑖𝑃𝑃𝑃𝑃𝐿𝐿 + 𝛽𝛽10𝑖𝑖𝑖𝑖𝑆𝑆𝐸𝐸𝑆𝑆𝐿𝐿
+ 𝛽𝛽11𝑖𝑖𝑖𝑖𝐶𝐶𝑃𝑃𝐿𝐿𝐸𝐸 + 𝛽𝛽12𝑖𝑖𝑖𝑖𝑃𝑃𝐿𝐿𝑆𝑆𝐿𝐿 + 𝛽𝛽13𝑖𝑖𝑖𝑖𝐸𝐸𝑀𝑀𝐸𝐸𝐸𝐸 + 𝛽𝛽14𝑖𝑖𝐸𝐸𝑓𝑓𝑑𝑑𝑐𝑐𝑠𝑠𝑡𝑡𝑓𝑓𝑒𝑒_𝐸𝐸
(9)
where i is the firm, j the country, t the year, and the previous defined variables.
In order to test the country level moderating effect of formal institutions I specify the following regression including the formal institutions interaction term:
𝐿𝐿𝐿𝐿𝐿𝐿𝑖𝑖𝑖𝑖𝑖𝑖 = 𝛼𝛼 + 𝛽𝛽1𝑖𝑖𝑖𝑖𝑀𝑀𝑀𝑀𝑀𝑀 + 𝛽𝛽2𝑖𝑖𝑖𝑖𝑀𝑀𝑀𝑀𝑀𝑀_𝐸𝐸 + 𝛽𝛽3𝑖𝑖𝑖𝑖𝑃𝑃𝐸𝐸 + 𝛽𝛽4𝑖𝑖𝑖𝑖𝑖𝑖(𝑀𝑀𝑀𝑀𝑀𝑀 ∗ 𝑃𝑃𝐸𝐸)
+ 𝛽𝛽5𝑖𝑖𝑖𝑖𝑀𝑀𝑀𝑀 + 𝛽𝛽6𝑖𝑖𝑖𝑖𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 + 𝛽𝛽7𝑖𝑖𝑖𝑖𝑃𝑃𝐸𝐸 + 𝛽𝛽8𝑖𝑖𝑖𝑖𝑃𝑃𝐸𝐸_𝐸𝐸 + 𝛽𝛽9𝑖𝑖𝑖𝑖𝑆𝑆𝐿𝐿
+ 𝛽𝛽10𝑖𝑖𝑖𝑖𝑆𝑆𝐿𝐿_𝐸𝐸 + 𝛽𝛽11𝑖𝑖𝑖𝑖𝑃𝑃𝑃𝑃𝐿𝐿 + 𝛽𝛽12𝑖𝑖𝑖𝑖𝑆𝑆𝐸𝐸𝑆𝑆𝐿𝐿 + 𝛽𝛽13𝑖𝑖𝑖𝑖𝐶𝐶𝑃𝑃𝐿𝐿𝐸𝐸
+ 𝛽𝛽14𝑖𝑖𝑖𝑖𝑃𝑃𝐿𝐿𝑆𝑆𝐿𝐿 + 𝛽𝛽15𝑖𝑖𝑖𝑖𝐸𝐸𝑀𝑀𝐸𝐸𝐸𝐸 + 𝛽𝛽16𝑖𝑖𝐸𝐸𝑓𝑓𝑑𝑑𝑐𝑐𝑠𝑠𝑡𝑡𝑓𝑓𝑒𝑒_𝐸𝐸
(10)
where i is the firm, j the country, t the year, and the previous defined variables.
Last, I use the following regression including the two legal origin interaction terms to obtain the moderating effect of a country’s legal origin:
𝐿𝐿𝐿𝐿𝐿𝐿𝑖𝑖𝑖𝑖𝑖𝑖 = 𝛼𝛼 + 𝛽𝛽1𝑖𝑖𝑖𝑖𝑀𝑀𝑀𝑀𝑀𝑀 + 𝛽𝛽2𝑖𝑖𝑖𝑖𝑀𝑀𝑀𝑀𝑀𝑀_𝐸𝐸 + 𝛽𝛽3𝑖𝑖𝑖𝑖𝐿𝐿𝑃𝑃_𝐸𝐸 + 𝛽𝛽4𝑖𝑖𝑖𝑖𝑆𝑆𝐶𝐶𝐸𝐸𝑀𝑀_𝐸𝐸 + 𝛽𝛽5𝑖𝑖𝑖𝑖𝑖𝑖(𝑀𝑀𝑀𝑀𝑀𝑀 ∗ 𝐿𝐿𝑃𝑃_𝐸𝐸) + 𝛽𝛽6𝑖𝑖𝑖𝑖𝑖𝑖(𝑀𝑀𝑀𝑀𝑀𝑀 ∗ 𝑆𝑆𝐶𝐶𝐸𝐸𝑀𝑀_𝐸𝐸) + 𝛽𝛽7𝑖𝑖𝑖𝑖𝑀𝑀𝑀𝑀 + 𝛽𝛽8𝑖𝑖𝑖𝑖𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 + 𝛽𝛽9𝑖𝑖𝑖𝑖𝑃𝑃𝐸𝐸 + 𝛽𝛽10𝑖𝑖𝑖𝑖𝑃𝑃𝐸𝐸_𝐸𝐸 + 𝛽𝛽11𝑖𝑖𝑖𝑖𝑆𝑆𝐿𝐿 + 𝛽𝛽12𝑖𝑖𝑖𝑖𝑆𝑆𝐿𝐿_𝐸𝐸 + 𝛽𝛽13𝑖𝑖𝑖𝑖𝑃𝑃𝑃𝑃𝐿𝐿 + 𝛽𝛽14𝑖𝑖𝑖𝑖𝑆𝑆𝐸𝐸𝑆𝑆𝐿𝐿 + 𝛽𝛽15𝑖𝑖𝑖𝑖𝐶𝐶𝑃𝑃𝐿𝐿𝐸𝐸 + 𝛽𝛽16𝑖𝑖𝑖𝑖𝑃𝑃𝐿𝐿𝑆𝑆𝐿𝐿 + 𝛽𝛽17𝑖𝑖𝑖𝑖𝐸𝐸𝑀𝑀𝐸𝐸𝐸𝐸 + 𝛽𝛽18𝑖𝑖𝐸𝐸𝑓𝑓𝑑𝑑𝑐𝑐𝑠𝑠𝑡𝑡𝑓𝑓𝑒𝑒_𝐸𝐸 (11)
where i is the firm, j the country, t the year, and the previous defined variables.
4. Results
The analysis of Column (1) in Table 5 provides evidence for hypothesis 1b that a higher level of multinationality causes a lower leverage ratio, since the estimated MNY coefficient is negative and significant at the 1% level. This provides preliminary evidence that the more multinational a firm is, the lower their leverage ratio will be by using less debt.
This table reports the univariate leverage regression estimates. The dependent variable is the firm’s leverage ratio (LEV). Key explanatory variables in this regression are: multinationality (MNY), the multinationality dummy that takes the value of one if a firm’s foreign sales ratio is greater than 30% and zero otherwise (MNY_D), formal institutions (FI), the legal origin dummy that takes the value of one if the legal origin is civil law and zero in case of common law (LO_D), the Scandinavian law dummy that equals to one if the legal origin is Scandinavian law and zero otherwise (SCAN_D). The sample period runs from January 2010 to December 2014. Standard errors are robust to heteroskedasticity and clustered at the firm level. The associated t-statistics are reported in parentheses. *, **, and *** Denote significance at the 10%, 5% and 1% levels, respectively. (1) (2) (3) (4) (5) MNY -0.000486*** (-5.44) MNY_D -0.0219*** (-3.41) FI -0.0158 (-1.61) LO_D 0.0330*** (5.34) SCAN_D 0.0209*** (3.85) Constant 0.525*** 0.517*** 0.525*** 0.474*** 0.495*** (56.97) (55.17) (30.79) (48.10) (59.91)
Industry and time
fixed effects Yes Yes Yes Yes Yes
N 4325 4325 4325 4325 4325
R2 0.078 0.074 0.072 0.078 0.074
Moreover, MNY_D in Column (2) reports a negative coefficient of -0.0219, which is significant at the 1% level. This implies that firms with a foreign sales ratio greater than 30% are 2.19% less levered compared to firms with a foreign sales ratio less than 30%.
In Column (3) the estimated coefficient of FI is not significant and hence does not have explanatory power. However, the variables used to measure a country’s legal origin reported in Column (4) and (5) are both significant at the 1% level. The dummy variable LO_D reports a positive and significant coefficient of 0.0330, which thus implies that firms in civil law countries are 3.30% more levered compared to firms based in common law countries. This is in line with the studies of La Porta et al. (1998) and La Porta et al. (2002). More specifically, the dummy variable SCAN_D has a coefficient of 0.0209, which is significant at the 1% level and thus suggest that firms in Scandinavian law countries are 2.09% more levered than the other firms in civil and common law countries. However, these models are simple univariate
negative association between measures of multinationality and the firm’s leverage ratio. To account for this, I proceed to a multivariate analysis in the next section.
4.1 Leverage regressions
In this section I regress the main relationship between multinationality and leverage along with other firm and country characteristics that prior studies have used.
Column (2) of Table 6 indicates that even with the inclusion of both firm and country control variables, the MNY coefficient, which is -0.000514, remains significant at the 1% level. This confirms hypothesis 1b and is in line with the studies of Doukas and Pantzalis (2003) and Burgman (1996). The finding is consistent with the explanation of the negative effects of agency costs on the MNCs leverage ratios. As a result of monitoring problems among geographically diversified MNCs, agency costs will occur where bondholders will demand higher interest payments on loans that are more exposed to information asymmetries and higher monitoring costs. This implies that MNCs tend to have lower levels of leverage when their level of foreign involvement is increasing. Moreover, this negative relationship is in line with the study of Burgman (1996) that considers the factor exchange rate risk among MNCs. Exchange rate changes trigger financial distress and thus pose substantial risk to MNCs, which results in lower levels of debt among MNCs. Furthermore, this negative relationship between the level of multinationality and a firm’s leverage ratio is in line with the study of Rego (2003) who reports that the effective tax rate for MNCs is significantly lower than their domestic counterpart. Following this reasoning, MNCs with a lower tax burden will have lower leverage ratios, since these firms have the ability to transfer earnings from high-tax countries to low-tax countries.
When all variables are included in Column (3) of Table 6, the negative MNY coefficient is still -0.000543 and highly significant at the 1% level. This implies that a 1% increase in the level of multinationality leads to a 0.0543% decrease in the firm’s leverage ratio. Overall, the impact of multinationality on the firm’s leverage ratio is statistically highly significant but in general small and thus economically less meaningful.
This table reports the multivariate leverage regression estimates including the control variables. The dependent variable is the firm’s leverage ratio (LEV). Key explanatory variables in this regression are: multinationality (MNY), the multinationality dummy that takes the value of one if a firm’s foreign sales ratio is greater than 30% and zero otherwise (MNY_D), formal institutions (FI), the legal origin dummy that takes the value of one if the legal origin is civil law and zero in case of common law (LO_D), the Scandinavian law dummy that equals to one if the legal origin is Scandinavian law and zero otherwise (SCAN_D). All variables are described in section 3.2 of this paper. The sample period runs from January 2010 to December 2014. Standard errors are robust to heteroskedasticity and clustered at the firm level. The associated t-statistics are reported in parentheses. *, **, and *** Denote significance at the 10%, 5% and 1% levels, respectively.
(1) (2) (3) MNY -0.000475*** -0.000514*** -0.000543*** (-3.68) (-4.23) (-4.43) MNY_D 0.00229 0.00383 0.00342 (0.25) (0.45) (0.40) FI -0.0750*** -0.0118 (-5.22) (-0.68) LO_D 0.0284*** 0.0429* (4.44) (1.67) SCAN_D 0.0463*** 0.0214** (5.79) (1.98) MB 0.0188*** 0.0190*** (11.04) (11.06) PROF -0.541*** -0.537*** (-13.88) (-13.80) RD -0.393*** -0.402*** (-4.40) (-4.43) RD_D -0.0251*** -0.0233*** (-4.33) (-3.97) SE -0.146*** -0.139*** (-7.21) (-6.91) SE_D 0.0392*** 0.0366*** (5.66) (5.24) PPE -0.0932*** -0.0940*** (-6.92) (-7.01) SIZE 0.0130*** 0.0134*** (9.76) (9.95) CRED -0.00764*** -0.000657 (-4.50) (-0.16) RESV -0.150*** -0.158*** (-8.84) (-7.98) ANTD -0.00727*** -0.000751 (-4.05) (-0.15) Constant 0.599*** 0.457*** 0.400*** (26.87) (20.93) (8.20)
Industry and time
fixed effects Yes Yes Yes
N 4325 4325 4325
R2 0.093 0.236 0.242
4.2 Results of a country’s formal institutions and legal origin
In addition to the main relationship between the level of multinationality and a firm’s leverage ratio, I next examine the two moderating effects of a country’s formal institutions and legal origin. Again all the coefficient estimates and corresponding t-statistics are estimated using standard errors robust to heteroskedasticity and clustered at the firm level. Both industry and year dummies are included to account for industry and time fixed effects. The results of these models including the interaction terms are presented in Table 7. Column (1) reports that the MNY*FI coefficient is positive and significant at the 1% level. This positive coefficient of the interaction term means that companies in countries with stronger formal institutions have a less negative relationship between multinationality and the firm’s leverage ratio compared to companies from countries with weaker formal institutions, due to the upward slope effect of the positive interaction term. These results provide evidence for hypothesis 2a that states that the effect of multinationality on the firm’s leverage ratio is stronger for companies based in countries with strong formal institutions. This is in line with the study of La Porta et al. (1998) and Qian and Strahan (2007) reasoning that strong formal institutions with strong creditor rights expand the availability of loans, since the presence of strong formal institutions in times of bankruptcy and reorganizations, provides the creditors with a certain level of assurance. Consequently, lenders are more willing to provide credit on favorable terms, which implies lower interest rates and higher leverage ratios among MNCs.
Column (2) shows that the MNY*LO_D coefficient is positive and significant at the 1% level. This positive coefficient of the interaction term implies that companies in civil law countries have a less negative relationship between multinationality and the firm’s leverage ratio compared to companies based in common law countries, due to the upward slope effect of the positive interaction term. This provides support for hypothesis 3 that states that the effect of multinationality on the firm’s leverage ratio is stronger for companies based in civil law countries. These results confirm the findings from La Porta et al. (1997) who show that firms in civil law countries rely on government regulations and ownership, whereas common law countries often rely on private contracting. As a consequence, civil law countries provides MNCs worse access to equity finance compared to common law countries, and this results that firms in civil law countries rely more on debt.
multinationality. Similar to the civil law countries, Column (3) reports that the MNY*SCAN_D is positive and significant at the 1% level. This positive coefficient of the interaction term implies that companies in Scandinavian law countries have a less negative relationship between multinationality and the firm’s leverage ratio compared to companies based in other civil or common law countries, due to the upward slope effect of the positive interaction term. These results are consistent with La Porta et al. (1997) reasoning that in contrast to common law, Scandinavian law can be considered as a legislator-made civil law tradition. This implies that Scandinavian law countries should report similar results as the other civil law countries since they rely on government regulation and ownership as well. By combining both the legal origin dummy and Scandinavian law dummy in one model, Column (4) reports that the MNY*SCAN_D coefficient remains significant at the 1% level. However, the MNY*LO_D is not significant and loses its explanatory power.
This table reports the leverage regression estimates including the moderating effects and control variables. The dependent variable is the firm’s leverage ratio (LEV). Key explanatory variables in this regression are: multinationality (MNY), the multinationality dummy that takes the value of one if a firm’s foreign sales ratio is greater than 30% and zero otherwise (MNY_D), formal institutions (FI), the interaction term between multinationality and formal institutions (MNY*FI), the legal origin dummy that takes the value of one if the legal origin is civil law and zero in case of common law (LO_D), the interaction term between multinationality and the legal origin dummy (MNY*LO_D), the Scandinavian law dummy that equals to one if the legal origin is Scandinavian law and zero otherwise (SCAN_D), the interaction term between multinationality and the Scandinavian law dummy (MNY*SCAN_D). The sample period runs from January 2010 to December 2014. Standard errors are robust to heteroskedasticity and clustered at the firm level. The associated t-statistics are reported in parentheses. *, **, and *** Denote significance at the 10%, 5% and 1% levels, respectively.
(1) (2) (3) (4) (5) (6) (7) MNY -0.00280*** -0.000912*** -0.000770*** -0.000955*** -0.00270*** -0.00223*** -0.00233*** (-5.06) (-4.92) (-5.86) (-5.14) (-4.88) (-3.00) (-3.12) MNY_D 0.0105 0.00470 0.00722 0.00717 0.00880 0.00894 0.00873 (1.24) (0.56) (0.86) (0.85) (1.03) (1.05) (1.02) FI -0.0416* -0.0660*** -0.0706* -0.0688* (-1.79) (-2.58) (-1.86) (-1.80) MNY*FI 0.00144*** 0.00124*** 0.00102** 0.000968* (4.17) (3.39) (2.02) (1.90) LO_D 0.0516*** 0.0216 0.0527** 0.0216 (2.74) (0.77) (2.30) (0.77) MNY*LO_D 0.000504*** 0.000299 0.000328* 0.000281 (2.76) (1.54) (1.70) (1.44) SCAN_D -0.0162 -0.0214 0.0127 0.00673 (-1.31) (-1.44) (0.63) (0.30) MNY*SCAN_D 0.000709*** 0.000605*** 0.000313 0.000234 (4.04) (3.26) (1.20) (0.89) MB 0.0185*** 0.0189*** 0.0187*** 0.0187*** 0.0189*** 0.0189*** 0.0189*** (10.81) (11.06) (10.94) (10.94) (11.04) (11.02) (11.02) PROF -0.535*** -0.534*** -0.535*** -0.533*** -0.533*** -0.537*** -0.535*** (-13.85) (-13.73) (-13.82) (-13.76) (-13.84) (-13.93) (-13.87) RD -0.380*** -0.396*** -0.396*** -0.396*** -0.395*** -0.405*** -0.405*** (-4.28) (-4.40) (-4.42) (-4.41) (-4.39) (-4.49) (-4.49) RD_D -0.0266*** -0.0239*** -0.0237*** -0.0236*** -0.0242*** -0.0237*** -0.0235*** (-4.61) (-4.12) (-4.10) (-4.06) (-4.15) (-4.06) (-4.01) SE -0.146*** -0.146*** -0.142*** -0.145*** -0.147*** -0.140*** -0.143*** (-7.24) (-7.26) (-7.00) (-7.19) (-7.30) (-6.93) (-7.11) SE_D 0.0397*** 0.0363*** 0.0381*** 0.0374*** 0.0385*** 0.0394*** 0.0387*** (5.71) (5.23) (5.53) (5.41) (5.54) (5.68) (5.56) PPE -0.0931*** -0.0941*** -0.0960*** -0.0958*** -0.0932*** -0.0944*** -0.0942*** (-6.96) (-7.05) (-7.18) (-7.17) (-6.98) (-7.04) (-7.03) SIZE 0.0137*** 0.0130*** 0.0137*** 0.0135*** 0.0134*** 0.0139*** 0.0137*** (10.14) (9.75) (10.26) (10.06) (9.95) (10.32) (10.12) CRED -0.00939*** 0.00399 -0.00716*** -0.00170 0.00274 -0.00635*** -0.000968 (-5.43) (1.41) (-4.23) (-0.43) (0.73) (-3.28) (-0.24) RESV -0.193*** -0.168*** -0.158*** -0.162*** -0.178*** -0.160*** -0.163*** (-10.70) (-10.00) (-9.47) (-9.71) (-9.62) (-8.17) (-8.35) ANTD -0.00731*** 0.00669** -0.00853*** -0.00133 0.00488 -0.00896*** -0.00196 (-4.05) (2.09) (-4.70) (-0.26) (1.26) (-4.83) (-0.39) Constant 0.520*** 0.355*** 0.456*** 0.412*** 0.455*** 0.550*** 0.504***
Industry and time fixed effects
(13.20) Yes (10.47) Yes (20.67) Yes (9.13) Yes (10.32) Yes (10.18) Yes (7.37) Yes N 4325 4325 4325 4325 4325 4325 4325 R2 0.243 0.243 0.245 0.246 0.245 0.245 0.246
5. Conclusion
This study raises the question whether the moderating effects in a country’s formal institutions and legal origin have any impact on the relationship between the level of multinationality and the firm’s leverage ratio. After conducting a regression analysis I found that the main relationship between the level of multinationality and the firm’s leverage ratio is negatively significant, meaning that MNCs with more foreign involvement have lower leverage ratios. Multinational firms have operations that are more geographically diversified, which makes them more complex in terms of collecting and processing information. As a result of these monitoring problems among MNCs, agency costs will occur and as argued before a higher level of foreign involvement will negatively impact the firm’s leverage ratio. This finding is consistent with the study of Doukas and Pantzalis (2003) who report that the agency costs of debt are positively and significant associated to the firm’s level of foreign involvement. Most importantly, my findings are consistent with the theory that MNCs are subject to higher agency costs as their level of foreign involvement increases. Following this theory MNCs will rely more on equity to overcome the agency costs of debt.
Overall, this study contributes to the international finance literature where the firm’s level of foreign involvement can be considered as one of the determinants of access to different sources of finance. The practical relevance of this study is that decisions made by managers regarding international capital structures can be used as an important source for directing the internationalisation of MNCs. International financial managers might take into account the negative relationship between the level of multinationality and the firm’s leverage ratio when considering a firm’s minimum credit rating of corporate bonds. As explained by Kisgen (2009), after a credit rating downgrade the significant lower leverage ratios of MNCs could be could be useful for financial managers to target the minimum credit rating at which certain investor groups are able to invest in a firm’s corporate bonds. Especially, considering the significant effect of a country’s formal institutions and legal origin, international financial managers can now make better decisions based on geographic and systematic predictions that are empirically confirmed by the results of this study.
6. Further research
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Appendix
This table presents all variables averaged at the country level. The following variables are used: leverage (LEV), multinationality (MNY), the multinationality dummy that takes the value of one if a firm’s foreign sales ratio is greater than 30% and zero otherwise (MNY_D), formal institutions (FI), the Scandinavian law dummy that equals to one if the legal origin is Scandinavian law and zero otherwise (SCAN_D), the legal origin dummy that takes the value of one if the legal origin is civil law and zero in case of common law (LO_D), market-to-book ratio (MB), profitability (PROF), R&D expenses (RD), the R&D dummy variable that equals one if the firm has R&D expenses and zero otherwise(RD_D), selling expenses (SE), the selling expenses dummy variable that equals one if the firm has selling expenses and zero otherwise(SE_D), property plant and equipment (PPE), firm size (SIZE), creditor rights (CRED), legal reserve requirements (RESV), shareholder rights (ANTD). The sample period runs from January 2010 to December 2014.
Country
No. of Obs.
No. of.
