capital structure and agency cost

Agency costs of stakeholdersand capital structure:international evidence

Bing YuSchool of Business, Meredith College, Raleigh, North Carolina, USA

Abstract

Purpose – This paper examines the relationship between bargaining powers of creditors as well asemployees and financial leverage across countries. The purpose of this paper is to explore roles ofcreditors and employees in capital structure decisions under different legal and political regimesacross countries.

Design/methodology/approach – Using country-level creditor rights index and labor rights indexas a proxy for bargaining powers of creditors and employees, respectively, the author addresses theinteraction between creditors as well as employees and shareholders. The paper tests the impact ofemployee rights and creditor rights on capital structure across countries.

Findings – The author finds a positive relationship between employee rights and firms’ use of debtand a negative relationship between creditor rights and firm debt ratio.

Social implications – The paper provides a new perspective to interpret international variation infinancial leverage in the world. The results obtained from this paper help us to understand financialleverage in different countries with various corporate governance mechanisms.

Originality/value – This paper takes all stakeholders into account when studying agency problems;it explores the role of creditors and employees in financing decision making under various corporategovernance patterns and political and legal systems across countries.

Keywords Corporate governance, Capital structure, Creditors, Employees, Agency problems,Creditor rights, Labor rights

Paper type Research paper

I. IntroductionA growing interest has been given to the impact of non-financial stakeholders such ascreditors and employees on corporate decisions in corporate finance literature. Thispaper examines relationship between creditors as well as employees and financialleverage across countries. The purpose is to explore roles of creditors and employees incapital structure decisions under different legal and political regimes across countries.

Shareholders, creditors, and employees have heterogeneous utility functions incorporate context. Tirole (2001, 2006) asserts that corporations select optimalinvestment and financing decisions within the constraints of legal and politicalenvironments to which they belong. Within a company, stakeholders bargain with eachother to maximize benefits of themselves. The bargaining between stakeholders is ruledand regulated by a country’s legal and political regime. While legal and political regimesdiffer across countries, the bargaining powers of stakeholders are not identical indifferent countries. Interaction between creditors and shareholders is mainly throughthe negotiation in debt contracting. The bargaining power of creditors relies largely

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JEL classification – G30, G32, G38, K3

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Managerial FinanceVol. 38 No. 3, 2012

pp. 303-324q Emerald Group Publishing Limited

0307-4358DOI 10.1108/03074351211201433

on creditor rights (CR) provided by a country’s legal system. Employees, on the otherhand, do not have voting right nor bargaining power unless they form unions or getprotection from labor law. Existing literature suggests that shareholders, with theconstraints of legal regime in a country, will seek a mechanism within corporations toweaken creditors and employees’ bargaining powers so as to maximize payoffs.Financial leverage is a tool that shareholders can use to achieve this goal. Dronars andDeere (1991) develop a model to describe the role of debt in limiting employees’bargaining power when they form unions, while Matsa (2010) finds that debt ispositively correlated with unionization rates at firm level for firms in the USA.

This paper focuses on cross-country comparison. Using country-level creditor rightand labor right indices as proxies for bargaining powers of creditors and employees,I investigate the impacts of creditor and employee rights on capital structure acrosscountries. I argue that when employee rights are high, employees will have strongerbargaining powers and shareholders are more likely to be exploited by employees.If so, shareholders intend to use more debt obligation to remove free cash flows so asto reduce amount of revenues employees can extract. When CR are high, creditors havemore negotiation power to obtain good terms in debt contracting. If shareholderscannot get a favorable debt contract, they are likely to reduce the use of debt capital.

My study extends the literature by exploring country level factors’ influences and bytaking creditors and employees’ roles into account when examining capital structuredecisions across countries. This paper is directly related to the capital structureliterature that makes cross-country comparison of financial leverage. Empirical researchon cross-country financial leverage finds a large variation across countries[1]. Basically,these studies merely document differences in capital structure in different countries orcountry groups. They identify how firm-level determinants of capital structure such asfirm size, profitability, market-to-book ratio, retained earnings, and growthopportunities affect capital structure differently across countries and interpretgenerally the empirical results based on agency problems or signaling theories,without examining specifically the impacts of creditors and employees on financialleverage across countries. Treating a firm as a nexus through which shareholders andmanagers in the productive enterprise contract with each other, law and financeapproach represented by a series of papers by La Porta, Lopez-deoSilanes, Shleifer, andVishny (LLSV hereafter) examines the relationship between a country’s legal origin aswell as level of protection for investors and finance. La Porta et al. (1997, 1998) find thatcommon law countries provide stronger protection for shareholders than civil lawcountries do and suggest that stronger investor protection has positive impact offinancial market development. Numerous studies apply this law and finance approachand link country-level shareholder rights (SR) to corporate finance decisions (Rajan andZingales, 1995, Claessens and Laeven, 2003, Hail and Leuz, 2006 and Pinkowitz et al.,2006). While prior research focuses on SR, this paper extends the literature by exploringcountry-level creditors and employees’ roles in capital structure decisions acrosscountries.

Around the world, countries with different legal and political systems providedifferent extent of supports for various stakeholders. Some countries are in favor ofshareholders or creditors whereas others are in favor of employees (Gourevitchand Shinn, 2005, Roe, 2004). This variation in legal and political institutions shapesthe characteristics of bargaining powers of various stakeholders (Charny, 1999).

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Therefore, shareholders’ efforts to interact with creditors and employees are constrainedby a country’s institutional conditions. Since creditor and employees rights granted bylaw and regulatory regime are exogenous, shareholders will seek reduction ofbargaining powers of creditors and employees within a corporation. Basically, whenshareholders use debt obligation to reduce free cash flows, employees are less likely toobtain explicit or implicit benefits ( Jensen, 1986; Dronars and Deere, 1991). In regard tocreditors, since stronger CR are in favor of creditors at expense of shareholders in debtcontracting, shareholders will choose to use less debt capital so as to mitigate thebargaining power of creditors.

My paper is also related in general to several studies that test the stakeholder theoryof capital structure at firm level. Klasa et al. (2009) and Matsa (2010) analyze thestrategic use of debt financing by firms in highly unionized industry areas in the USAand find that those firms use more debt to remove free cash so as to gain bargainingadvantages over employees and protect firms from exploit of unions. Myers andSaretto (2009) find that firms increase leverage in response to the possibility of unionstrikes when bargaining power of unions is strong. Both Acharya et al. (2011) and Vig(2011) find that in countries with stronger CR firms have lower financial leverage. Theyassert that firms are reluctant to use debt when CR are strong because financialdistress costs are too high under such a situation.

In line with the above studies, I argue that across countries, firms in countries withstronger employee rights will use more debt while firms in countries with stronger CRare likely to use less financial leverage. Shareholders will use financing strategydifferently to mitigate bargaining powers of creditors and employees, restricted byextents of creditor and employee rights provided by a country’s legal regime. When afirm has less free cash flows, employees are less likely to obtain extra benefits from thefirm even the labor law and regulatory regime provide high employee right in thatcountry. When shareholders intend to use financial leverage to break employees andmanagers’ preference for overexpansion and excessive risk reduction, anotherstakeholder, creditors, will get involved. Unlike employees whose human capital is tiedup in the firm and not well diversified, creditors can diversify their investment well.Thus, within legal framework, creditors can protect themselves through debtcontracting. Depending on the creditor right provided by a country’s legal regime,creditors can negotiate with shareholders in such terms as cost of borrowing, limitationon dividends payment in some circumstances, and restriction on excess borrowing inthe presence of high debt ratio.

This study addresses the following research questions:

RQ1. What is the relationship between country-level employee rights andcorporations’ financial leverage across countries?

RQ2. What is the relationship between CR and corporations’ financial leverageacross countries?

While exploring the role of creditors and employees in financing decision making undervarious corporate governance patterns and political and legal systems across countries,this paper provides a new perspective to interpret international variation in financialleverage in the world. The results obtained from this paper help us to understandfinancial leverage in different countries with various corporate governance mechanismsand fill significant gaps in the literature on capital structure.


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The rest of the paper is organized as follows. A conceptual framework is discussedand testable hypotheses are developed in Section I. Section II describes data andresearch methodologies. Section III discusses empirical results. Section IV concludesthe study.

II. Conceptual frameworkWhile shareholders can reduce their investment risk via diversification, employees tietheir human capital to a corporation. This asymmetric risk reduction betweenshareholders and employees induces different risk aversion levels of shareholders andemployees. The contradictory preferences and pursuits between shareholders andemployees induce employees to seek for protection for their interests and job securitythrough any available channels. The most direct way employees use to protect theirbenefits is labor contracting. However, contracting involves negotiation and bargain.Unlike shareholders, employees have a lower bargaining power in contracting processunless they form union to get collective bargaining power. A union can extract no morethan the present value of future net cash flows. Dronars and Deere (1991) state thatfirms can use debt to limit the effect that a union has on shareholder wealth becausedebt obligation requires firms to repay a portion of future revenues to creditors, andhence limit the amount of cash that employees can extract through a union’s strongbargaining power, without driving the firm into bankruptcy.

Roe (2003) asserts that governments provide protection for employees through theirlaw regulation in such areas as union formation, the costs of firing employees, and thedifficulties of firing employees. When employees obtain more benefits resulting fromstronger employee protection provided by a country’s labor law and regulation,shareholders suffer from the increased revenues extracted by employees due to strongeremployee right. Therefore, shareholders have incentives to use more debt to divertfuture cash flows to themselves rather than to employees.

With stronger bargaining powers either through formation of labor unions or from acountry’s legal regime, employees and creditors will bargain with shareholders topursue their best payoff. Since employee and CR are granted by a country’s legal regime,shareholders will choose to lessen employees and creditors bargaining powers throughfirm-level decisions. Using financial leverage is an effective way at firm level to mitigatebargaining powers of creditors and employees.

Based on the above discussion, financial leverage is regarded as a tool to limitbargaining powers of creditors and employees. The extent of bargaining powersdepends on the level of employee protection, SR, and CR provided by a country’s legaland regulatory regime. Thus, I explore the association between country-level employeeand CR and financing via testing hypotheses. Using country-level labor right as aproxy for employee protection (Botero et al., 2004) and creditor right as proxy forcreditor protection (LLSV, 2006), I hypothesize:

H1. The stronger the labor right, the more debt the company will use.

A legal and political system that provides strong employee protection will emphasizeemployees and managers’ natural agenda and demeans shareholders’ nature agenda.Strong employee protection makes it hard and costly to lay off employees. Therefore,under such a system, the pressure on the firm for low risk, unprofitable expansionis high, and the pressure to avoid risky organizational change is substantial.

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However, shareholders would prefer to go slow in expanding the firm, becauseexpansion is harder to reverse later than it would be in a political environment thatprovides weak employee protection. To avoid unprofitable expansion and to eliminatethe possibility of raising employees’ salaries and benefits, shareholders want to removefree cash flows from the firm via using more interest-bearing debts. When a country’slegal regime is in favor of employees, in order to weaken bargaining power of employees,corporations will choose to use more debt:

H2. The stronger the creditor right, the less the debt the company will use.

Creditor can influence a firm’s financing decision through debt contracting. The strongerthe creditor right, the more negotiating power creditors have during contracting process.High creditor right allows creditors more likely to obtain favorable contracting.To reduce bargaining power of creditor, shareholders are likely to use less debt capital.

III. Data and methodologies3.1 Data sources and sample selectionThe primary data source for the paper is Compustat Global Vantage. All firm-levelfinancial accounting variable data are obtained from Global Industrial file. Marketprice data are collected from Compustat Global Issue file. Country currency exchangerate data are from Compustat Global Currency File. Country-level data are collectedfrom various resources. Country-level variables are obtained from previous research ineach aspect, respectively. I obtained SR, CR, and (LR) data from Djankov et al. (2008),Djankov and Shleifer (2007) and Botero et al. (2004), respectively. I collected macroeconomic data including stock market capitalization, bond market capitalization,banking segment, GDP growth rate, inflation rate from IMF and World Bank annualstatistics. Government quality data are from Kaufmann et al. (2007). Table I lists dataand variable information.

The sample period is 1990-2008. I begin sample construction by matchingCompustat Global Industrial with Global Issue and Global Currency files.

Rajan and Zingales (1995) point out that in any studies that compare corporations’financial data across countries, the differences in accounting practices cause samplesbias. They notice that not every country requires firms to report consolidated balancesheets, and corporations with unconsolidated balance sheets appear to haveunderestimated financial leverage data than those with consolidated financialstatements. To avoid this sample selection bias, I select firms with fully consolidatedaccounting statements only (consol ¼ F in Global Industrial file). Since firms involved inmajor mergers (cstat ¼ AB in Global Industrial file) have special capital structure(Aivazian et al., 2001), such firms are dropped. Following literature on capital structure(Rajan and Zingales, 1995; Aivazian et al., 2001), I exclude financial firms (6999 . SICcode . 6000), and utility firms (4999 . SIC code . 4900). I also drop firms withnegative equity, negative sales revenue, missing value of total assets, and negative cashflows.

I match firm-level data from Global Vantage with country-level data from variousresources and require main three country-level explanatory variables, SR, CR, and laborrights (LR) indices, be available to each country included in our sample. To comply withthe requirements of time-series cross-sectional regression, I drop the following countrieswith less than 30 firm-year observations, Ghana, Croatia, Jordan, Kenya, and Romania.


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After applying these filters, our sample contains 182,182 firm-year observations from21,663 unique firms over 52 countries during the period of 1990-2008.

I use two country-level variables, CR and LR indices as proxies for the bargainingpowers of creditors and employees, respectively. The SR is used as a control variable.

LLSV (1998) develop a SR index. This SR index is widely used in literature (LLSV,2000; Pinkowitz et al., 2006). Djankov et al. (2008) update La Porta et al. (1997) SR indexto make it more accurate. I use the updated anti-self-dealing index from Djankov et al.(2008) as a proxy for SR.

Similar to SR index, Djankov and Shleifer (2007) use CR index to measure forcountry-level protection for creditors. The CR index is an accumulation of four dummyvariables that check:

. whether a country imposes restrictions, such as creditor’s consent or minimumdividends to file for reorganization;

. whether secured creditors are able to gain possession of their security once thereorganization petition has been approved (no automatic stay);

. secured creditors are ranked first in the distribution of the proceeds that resultfrom the disposition of the assets of a bankrupt firm; and

Abbr. Measurement Source

Panel A: firm-level variablesVariable

Debt Debt ratio Long-term debt/total assets Global Industrial fileMTB Market-to-book ratio (BV of total assets-BV of

equity þ MV of equity)/total assetsGlobal Industrial andGlobal Issue

Profit Profitability EBITDA/total assets Global Industrial fileCash Cash Cash balance/total assets Global Industrial fileSize Size Log of total assets in US dollars Global Industrial fileTang Tangibility Tangible assets/total assets Global Industrial filePanel B: country-level variables

Proxy forSR Shareholder rights Anti-self-dealing index Djankov et al. (2008)CR Creditor rights Creditor rights index Djankov and Shleifer

(2007)LR Labor rights Labor union power index Botero et al. (2004)Stock Market Stock market

developmentStock market capitalization/GDP World Bank report

GOV_QUAL Government quality Government quality index Kaufmann et al. (2007)OWNER_CON Ownership structure Ownership concentration index LLSV (1998)BDGDP Bond market

developmentPrivate bond market capitalization/GDP

World Bank report

GDPG Economicdevelopment

Annual GDP growth rate World Bank report

Inflation Inflation Annual inflation rate World Bank reportBKGDP Banking

developmentDomestic bank deposits/GDP IMF Statistic report

COM Legal origin Dummy variable equals one forcommon law origin countries and zerootherwise

LLSV (1998)Table I.Data definitions,measurements andsources

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. whether the debtor does not retain the administration of its property pending theresolution of the reorganization.

Roe (2004) asserts that a marginal increase in benefits of employees would be amarginal decrease in shareholders’ value and that strong LR provided by legal andpolitical systems in fact hurt a firm value. Therefore, I use measures for LR as a proxyfor bargaining power of employees.

There is an extensive literature on the relationship between LR and law andregulation of labor (Besley and Burgess, 2003; Heckman and Pages-Serra, 2000; Lazear,1990). Those studies check the law and regulatory provisions on such aspects as thedifficulty of firing employees, the costs of firing employees, and the easiness of hiringemployees and explore how employees’ benefits are affected due to the differences inthose provisions. With regard to employees’ power to pursue maximum benefits,Botero et al. (2004) use the labor union power index as a proxy for LR. The labor unionpower is an average of seven dummy variables which equal one:

(1) if employees have the rights to unionize;

(2) if employees have the rights to collective bargaining;

(3) if employees have the legal duty to bargain with unions;

(4) if collective contracts are extend to third parties bylaw;

(5) if the law allows closed shops;

(6) if workers or unions, or both, have a right to appoint members to the Boards ofDirectors; and

(7) if workers’ councils are mandated by law.

3.2 Methodology and research designStudies on financial leverage based on the trade-off theory and the pecking ordertheory use the partial adjustment model to explore the optimal debt ratio (Harris andRaviv, 1990; Myers, 2001) whereas studies addressing agency problems use debt ratioto regress on firm-level determinants (Myers and Majluf, 1984). Studies oninternational capital structure test the different impact of firm-level factors and addcountry-level variables as explanatory variables. Following Rajan and Zingales (1995)and Aivazian et al., I use the following model to examine the impact of creditor andemployee rights on financing decisions across countries:

Debtt ¼ a1 þ a2MTBt þ a3Profitt þ a4CASHt þ a5Sizet þ a6Tangt þ a7SRþ a8CR þ a9LR þ 1t ð1Þ

Debtt – the long-term debt ratio, computed by long-term debt divided bytotal assets for firm i at year t (firm subscription is suppressed inequation (1)).

MTBt – the market-to-book ratio, computed by the book value of total assetsminus the book value of equity plus the market value of equity all dividedby the book value of total assets for firm i at year t (firm subscription issuppressed in equation (1)).


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Profit – computed by earnings before interest, taxes, depreciation, andamortization (EBITDA) divided by total assets for firm i at year t (firmsubscription is suppressed in equation (1)).

Sizet – the log of total assets in US dollars for firm i at year t (firm subscription issuppressed in equation (1)).

Tangt – the tangibility computed by tangible assets divided by total assets forfirm i at year t (firm subscription is suppressed in equation (1)).

SR – the SR index at country level.

CR – the CR index at country level.

LR – the LR index at country level.

Rajan and Zingales (1995) point out that to examine the agency problems associatedwith debt, it is necessary to remove liabilities like accounts payable that is used fortransactions purpose rather than for financing purpose. Therefore, long-term debt ratiois a more reliable measure used to address agency problems. Following this logic, I uselong-term debt only as the dependent variable. Frank and Goyal (2005) argue thattheoretically, the book value of debt is a better measure of creditors’ liability in case ofbankruptcy than market value of debt and that market value of debt has measurementproblems due to the volatility of market price. Thus, the dependent variable, Debt, iscomputed by book value of long-term debt divided by book value of total assets foreach firm i at year t.

As discussed in Section I, this is a research that focuses on the impact ofcountry-specific characteristics on financing policy, I use two groups of independentvariables in empirical tests: firm-level variables and country-level variables. Twocountry-level variables, the CR and LR indices are major explanatory variables toaddress research objectives. Firm-level variables are used as control variables. Thefirm-level variables are selected based on capital structure theories, following up theliterature on capital structure.

Based on the capital structure theories, empirical research tests the impacts ofvarious variables on financial leverage and interprets test results using one or anothermodel. Chen and Zhao (2006) find that market-to-book ratio and profit are two keyfirm-level determinants of capital structure in various scenarios. Frank and Goyal (2005)examine 39 factors relating to financial leverage and divide those factors into two tiersbased on their reliability of relationships with leverage. The top-tier factors include firmsize, average leverage in an industry, risk, and market-to-book ratio. To study capitalstructure in the international context, considering availability of data for cross-nationalcomparison, Rajan and Zingales (1995) limit their firm-level control variables to fourfactors: tangibility of assets, the market-to-book ratio, firm size, and profitability.They argue that those are factors most consistently correlated with leverage in theliterature.

Consistent with Rajan and Zingales (1995) and Frank and Goyal (2005), I choose touse the follow firm-level variables as control variables: market-to-book ratio, profit,size, and tangibility. The market-to-book ratio (MTB) is widely used in literature(Rajan and Zingales, 1995; Aivazian et al., 2001; Chen and Zhao, 2006) to measure forgrowth opportunities. I use the book value of total assets minus the book value

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of equity plus the market value of equity all divided by the book value of total assets tocalculate the market-to-book ratio. Market value of equity is computed by stock pricemultiplying number of shares outstanding. Stock price information is collected fromGlobal Issue file. All stock prices are currency exchange rate-adjusted. Profit is definedas the ratio of EBITDA to total assets. Profit is a proxy for internal finance capacity asthe pecking order model suggests. Size is the log of total assets in US dollars.Tangibility, Tang, is computed by tangible assets divided by total assets. Both sizeand tangibility represent for corporations’ operating performance. Size is also used as aproxy for growth.

IV. Empirical results4.1 Summary statisticsI provide sample description and summary statistics in Tables II and III, respectively.The sample mean of debt ratio is 12.5 percent and median is 12 percent. Norway hasthe highest average debt ratio, 23.13 percent, whereas Morocco has the lowest debtratio, 5.31 percent over the sample period. As presented in the following section, theregression analysis on firm determinants of debt shows that those firm-level variablesaffect debt ratios across countries in a similar way, implying that it is country-specificcharacteristics that cause variations in financial leverage across countries.

Table IV presents variables that describe country characteristics. I divide sampleinto two groups: common law and civil countries. Consistent with literature, commonlaw countries have better shareholder protection than civil law countries because SRmean for common law and civil law countries is 0.736 and 0.377, respectively. The LRmean for common law and civil law countries is 0.261 and 0.340, respectively,indicating that higher employee rights in civil countries.

4.2 Firm-level determinants of financial leverageI start analysis by running regression using firm-level variables only. To address theoutliers issue, I winsorize all firm-level variables at 5 percent level[2]. I run thefixed-effect regression using panel data as follows (firm subscription suppressed):

Debtt ¼ a1 þ a2MTBt þ a3Profitt þ a4CASHt þ a5Sizet þ a6Tangt þ 1t ð2Þ

The variables are defined the same as in Section II. To test firm determinants of debtratio, one needs to adjust to industry effect either by subtracting industry mean(Chui et al., 2002) or by using industry dummy variables. Here, instead, I run theregressions using industry segment data and pooled sample. I run regression usingsub-samples, dividing sample groups based on industry segments first (Frank andGoyal, 2005). Then I run the pooled sample using industry fix effect model. Thesignificance of coefficients remains consistent, showing that the correlation betweendebt ratio and firm-level factors is not driven by industry difference. Table V presentsthe regression results.

As predicted by the agency costs model and the pecking order model, the empiricalresults are consistent with the literature on international capital structure comparison(Rajan and Zingales, 1995; Aivazian et al., 2001). There are conflicting theoreticalpredictions and mixed empirical findings on the effect of size on leverage. Rajan andZingales (1995) point out that firm size is usually regarded as a proxy both forinformation asymmetry and for the probability of bankruptcy. These two proxies


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CountryNo. of obs No. of obs No. of obs No. of obs No. of obsPrimary Manufacturing Advanced manufacturing Services Total

Argentina 5 99 74 37 215Australia 3,108 1,068 1,061 3,239 8,476Austria 95 219 269 201 784Belgium 110 305 270 313 998Brazil 37 433 426 257 1,153Canada 1,924 1,170 1,059 3,297 7,450Switzerland 36 437 938 634 2,045Chile 43 293 155 271 762China 241 1,679 2,387 1,790 6,097Colombia 0 44 39 33 116Czech Republic 12 24 16 40 92Germany 176 1,182 2,281 2,367 6,006Denmark 77 389 396 514 1,376Egypt 0 16 22 10 48Spain 186 387 327 424 1,324Finland 39 308 470 379 1,196France 324 1,352 1,783 2,766 6,225UK 1,583 2,855 3,347 9,078 16,863Greece 95 199 182 278 754Hong Kong 57 272 367 800 1,496Hungary 6 60 45 56 167Indonesia 145 810 459 580 1,994India 5 394 337 242 978Ireland 118 168 104 300 690Israel 6 100 93 130 329Italy 141 509 754 568 1,972Japan 2,332 6,054 11,238 14,899 34,523Korea 91 509 762 452 1,814Sri Lanka 0 9 0 31 40Morocco 0 8 19 5 32Mexico 91 229 151 316 787Malaysia 825 1,834 2,005 2,259 6,923The Netherlands 119 497 529 941 2,086Norway 191 237 347 621 1,396New Zealand 26 168 75 481 750Pakistan 20 159 85 29 293Panama 0 2 13 18 33Peru 60 30 41 28 159Philippines 212 247 152 381 992Poland 45 84 92 67 288Portugal 61 143 86 148 438Russian Federation 28 40 21 50 139Singapore 258 564 1,293 1,890 4,005Slovak Republic 13 19 7 0 39Sweden 174 408 824 1,067 2,473Thailand 165 1,034 754 1,087 3,040Turkey 11 89 155 79 334Taiwan 185 967 3,499 907 5,558USA 2,719 8,915 15,265 17,451 44,350

(continued )Table II.Sample description

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imply two inverse effects on leverage. However, coefficients of size are positivelysignificant. The coefficients of market-to-book ratios are negatively significant at1 percent level in services industry segment and pooled sample. While the results intable show that the firm-level determinants of capital structure across countries areconsistent, given the variations in capital structure around the world (Aggarwal, 1990;Aivazian et al., 2001; Gaud et al., 2007), it is necessary to explore the impact of countrycharacteristics on capital structure across countries.

4.3 The impact of creditor and employee rights on financing policyBased on the conceptual framework and hypotheses developed in Section I, I turn toexplore the relationship between creditor and employee rights and corporationsfinancing policy across countries. The analysis is implemented by running the pooledsample ordinary least square (OLS) regression with year and industry fixed effects.

Robust clustering standard errors are estimated to control for interdependenceacross firms. Based on Campbell (1996) and LLSV (2000), I introduce seven industrygroup dummies in cross-national regression to control for the industry effects[3]. Thereference group is the agriculture industry group.

The H1 in Section I predicts the positive sign for LR and the negative sign for CR.Table VI presents the regression results.

The pooled sample fixed effects regression generates positive LR coefficients,statistically significant at 1 percent level, and negative CR coefficients at 1 percentsignificant level. Model (1) tests the impacts of CR and LR on debt ratio only whereasmodel (2) adds SR as an additional independent variable. The results are significantafter controlling for firm-level factors, firm clustering effects, and the compoundedimpacts of SR, CR, and employee rights[4].

To address the possible presence of heteroscedasticity and autocorrelation, I alsoestimate the regression model with the Newey-West standard error. The results staystatistically significant.

To address the multicollinearity issue in OLS regression, I use variance inflationfactor (VIF) and tolerance to diagnose multicollinearity problem. Wooldridge (2002)defines the VIFs and tolerance as the following:

VIF ðbiÞ ¼ 1=ð1 2 R2i Þ; and

Tolerance ðbiÞ ¼ 1=VIF ¼ 1 2 R2i

where bi is the coefficients of model and Ri2 is the unadjusted R 2.

CountryNo. of obs No. of obs No. of obs No. of obs No. of obsPrimary Manufacturing Advanced manufacturing Services Total

Venezuela 0 31 32 20 83South Africa 332 241 228 1,168 1,969Zimbabwe 7 7 0 18 32Total 16,534 37,297 55,334 73,017 182,182

Notes: Primary industry: SIC: 0000-1999; manufacturing industry: SIC: 2000-2999; advancedmanufacturing industry: SIC: 3000-3999 services industry: SIC: 4000-9999 Table II.


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Country MTB Profit Size Tang Debt

Argentina 5.869 0.116 6.817 0.495 0.1279Australia 1.725 0.013 4.249 0.375 0.1117Austria 1.225 0.098 5.689 0.323 0.1172Belgium 1.415 0.118 6.126 0.293 0.1465Brazil 1.128 0.125 6.919 0.458 0.1288Canada 1.696 0.079 5.552 0.465 0.1690Switzerland 1.362 0.110 6.405 0.337 0.1551Chile 1.257 0.112 5.983 0.506 0.1293China 1.420 0.073 5.619 0.391 0.0680Colombia 0.921 0.067 6.694 0.398 0.0769Czech Republic 1.101 0.137 6.695 0.568 0.0794Germany 1.417 0.105 5.731 0.256 0.0956Denmark 1.399 0.104 5.567 0.327 0.1544Egypt 1.948 0.184 6.168 0.489 0.1993Spain 1.438 0.109 6.453 0.370 0.1224Finland 1.339 0.119 6.081 0.321 0.1939France 1.404 0.111 6.005 0.200 0.1294UK 1.687 0.092 4.909 0.320 0.0984Greece 1.747 0.133 5.669 0.363 0.1127Hong Kong 1.229 0.063 5.808 0.335 0.0855Hungary 1.266 0.120 5.538 0.454 0.0869Indonesia 1.291 0.128 4.634 0.415 0.1570India 1.891 0.147 5.516 0.337 0.1895Ireland 1.720 0.083 5.117 0.348 0.1518Israel 2.059 0.095 5.801 0.240 0.1159Italy 1.194 0.087 6.588 0.265 0.1182Japan 1.215 0.060 6.201 0.301 0.1244Korea 1.068 0.099 7.456 0.408 0.1838Sri Lanka 1.043 0.101 4.634 0.447 0.0883Morocco 2.256 0.243 6.599 0.344 0.0531Mexico 1.110 0.126 7.103 0.529 0.1709Malaysia 1.420 0.085 4.712 0.374 0.0799The Netherlands 1.587 0.131 5.917 0.292 0.1237Norway 1.517 0.092 5.455 0.359 0.2313New Zealand 1.538 0.125 4.993 0.440 0.2021Pakistan 1.371 0.170 4.621 0.420 0.0949Panama 1.761 0.108 8.769 0.553 0.2031Peru 0.853 0.168 5.654 0.467 0.0992Philippines 1.107 0.072 4.914 0.407 0.1183Poland 1.447 0.130 5.405 0.419 0.0609Portugal 1.207 0.102 6.021 0.409 0.1780Russia 1.167 0.180 8.320 0.567 0.0968Singapore 1.348 0.078 4.849 0.334 0.0916Slovak 1.010 0.151 6.332 0.550 0.0899Sweden 1.498 0.078 5.726 0.269 0.1426Thailand 1.245 0.110 4.396 0.429 0.1213Turkey 1.896 0.180 6.285 0.335 0.0716Taiwan 1.557 0.092 5.929 0.348 0.1156USA 1.899 0.096 5.849 0.285 0.1641Venezuela 0.831 0.110 6.081 0.505 0.1261

(continued )

Table III.Firm-level variables foranalyses

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It is readily seen that the higher VIF or the lower the tolerance index, the higher thevariance of bi and the greater the chance of finding bi insignificant, which means thatsevere multicollinearity effects are present. Thus, these measures can be useful inidentifying multicollinearity. Table VII presents the test result and VIF does not showserious multicollinearity problem.

The regression results reveal a positive relationship between LR and financialleverage level and a negative relationship between CR and the usage of debt financing.As discussed in Section I, when employees get strong protection from high LR, theymore easily obtain benefits from corporations through union negotiation or governmentintervention. Such employees’ benefit gain is at expense of shareholders. Sinceprotections for employees are exogenous, shareholders will seek a way within thecorporation to protect them from exploiting by employees. Using higher financialleverage to remove the free cash flow is one option shareholders can choose to achievethis goal. When I add SR index as an additional control variable, the coefficients of LRstay positively and increase substantially. They increased from 0.0185 to 0.043, andfrom 0.0193 to 0.0506 in two estimations, respectively. The increased positivecoefficients of LR in model (2) imply that in a country where SR are higher, it is morelikely that shareholders will use high financial leverage to mitigate agency costsof employees if such agency costs are caused by government law and regulatoryregimes.

The negative coefficient of CR suggests that CR affect corporations’ financingdecisions differently than LR. Unlike employees, creditors involve in debt contractingdirectly. In a country where CR are strong, creditors have more power to negotiate withshareholders and corporations to obtain better terms in debt contract or can easilyapply restrictions to corporations. Such restrictions might include the one that limitscorporation to use excess debt. On the other side, corporations and shareholders willchoose to use less debt since it is harder to get a favorable debt contract if CR arestrong. This result also supports the H2, which says the stronger the CR, the less debtthe firm will use.

4.4 Robust checkRegression analyses that use international sample are likely to generate biased resultsdue to the sample selection bias and the model misspecification (omitting variable)bias. In robust tests, I address the first issue by running the two-stage residual

Country MTB Profit Size Tang Debt

South Africa 1.516 0.146 5.701 0.376 0.0653Zimbabwe 2.210 0.244 5.069 0.334 0.1080Sample mean 1.664 0.115 5.872 0.387 0.125Sample median 1.416 0.110 5.804 0.375 0.120

Notes: Sample period is 1990-2008; the dependent variable Debt is the long-term debt ratio computedby long-term debt divided by total assets; MTB is the market-to-book ratio computed by the bookvalue of total assets minus the book value of equity plus the market value of equity all divided by thebook value of total assets; Profit is computed by EBITDA divided by total assets; Size is the log of totalassets in US dollars; Tang is the tangibility computed by tangible assets divided by total assets Table III.


315

regression (Hoeffler, 2002; Chui et al., 2002) and overcome the second bias by includingadditional control variables.

The major research objective of this paper is to examine the impacts of country-levelCR and employee rights on financing across countries, using firm-level variables ascontrol variables. The pooled sample regressions have two limitations. First, runningpooled sample regression cannot totally remove the disturbance of firm-level variables.Second, including all countries in the sample results in unequal weights in sample.

Country SR CR LR GOV_QUL ECO_GLB GDPG Inflation Bank BondStock

Market

Panel B: civil law countriesArgentina 0.34 1 0.3 20.74 3.24 20.284 7.83 0.274 0.047 0.316Austria 0.21 3 0.52 1.53 5.13 1.945 1.5 1.230 0.328 0.196Belgium 0.54 2 0.6 1.32 5.5 1.945 1.58 1.172 0.449 0.570Brazil 0.27 1 0.25 0 3.44 0.87 9.33 0.577 0.087 0.310Switzerland 0.27 1 0.25 1.45 5.16 0.98 0.86 1.716 0.439 1.891Chile 0.63 2 0.12 1.41 4.63 3.779 4.1 0.546 0.159 0.865China 0.76 2 0.14 20.19 3.16 8.156 0.37 0.063 0.315Colombia 0.57 0 0.078 0.1 3.41 1.244 9.12 0.353 0.005 0.178Czech Republic 0.33 3 0.3 0.95 4.41 0.742 2.88 0.589 0.046 0.233Germany 0.28 3 0.38 1.39 4.35 1.698 0.82 1.346 0.461 0.385Denmark 0.46 3 0.8 1.81 4.42 1.618 2.13 0.962 1.099 0.486Egypt 0.2 2 0.27 20.44 3.41 2.74 3.41 0.709 0.300Spain 0.37 2 0.13 1.06 4.81 2.068 3.81 1.172 0.228 0.566Finland 0.46 1 0.84 1.7 5.15 2.424 1.52 0.714 0.284 0.902France 0.38 0 0.09 1.06 4.79 1.728 1.41 1.040 0.450 0.606Greece 0.22 1 0.354 0.79 4.65 1.451 3.45 0.738 0.023 0.389Hungary 0.18 1 0.66 1.1 4.58 1.565 8.69 0.447 0.020 0.192Indonesia 0.65 2 0.012 20.26 3.54 3.853 12.4 0.446 0.014 0.223Italy 0.42 2 0.4 0.84 3.64 1.99 2.48 0.870 0.358 0.340Japan 0.5 2 0.24 1.27 4.16 2.247 21.73 2.070 0.439 0.787Korea 0.47 3 0.138 0.7 3.64 5.763 1.94 0.712 0.465 0.477Morocco 0.56 1 20.15 3.14 1.4 0.87 0.528 0.278Mexico 0.17 0 0.4 0.43 3.55 1.335 9.7 0.314 0.074 0.282The Netherlands 0.2 3 0.28 1.65 5.57 1.726 3.42 1.339 0.416 0.946Norway 0.42 2 0.8 1.34 4.64 2.489 4.86 0.716 0.215 0.378Panama 0.16 4 0.12 0.33 4.35 1.358 0.55 0.710 0.215Peru 0.45 0 0.05 0.11 3.85 20.037 2.36 0.195 0.024 0.240Philippines 0.22 1 0.12 20.06 3.17 0.443 5.59 0.429 0.003 0.491Poland 0.29 1 0.13 0.64 3.67 3.18 3.8 0.322 0.000 0.145Portugal 0.44 1 0.35 1 4.86 2.787 3.7 1.144 0.188 0.312Russia 0.44 2 0.63 20.45 3.07 20.063 31.22 0.220 0.000 0.293Slovak Republic 0.29 2 0.5 1.08 4.22 1.063 5.55 0.565 0.000 0.074Sweden 0.33 1 0.9 1.44 5.05 1.689 1.61 0.721 0.476 0.895Turkey 0.43 2 0.12 0.21 3.75 1.429 45.38 0.289 0.002 0.189Taiwan 0.56 2 0.35 0.94 5.691 21.11 0.218 1.013Venezuela 0.09 3 0.28 21.35 3.13 21.5 26.31 0.144 0.004 0.091Civil law mean 0.377 1.722 0.340 0.667 4.150 1.986 6.159 0.745 0.215 0.455Civil law median 0.375 2.000 0.280 0.890 4.220 1.694 3.415 0.710 0.159 0.316Sample mean 0.487 1.981 0.315 0.720 4.240 2.176 7.626 0.792 0.211 0.605Sample median 0.440 2.000 0.270 0.925 4.330 1.936 2.945 0.714 0.150 0.400

Table IV.SR, CR, and LR indicesand country-level controlvariables

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Some countries such as the USA, Britain, and Japan have a much larger number ofobservations than other countries do. Consequently, the results cannot excludethe excess impact of those big countries. To overcome such limitations, I use atwo-stage regression model to remove the firm-level factors and to exclude the sampleselection bias.

In the first stage, following Chui et al. (2002), I construct an adjusted dependentvariable by following method. First, debt ratio for firm i at year t in county j is estimatedby the following Default (firm and county subscription suppressed):

Debtt ¼ a1 þ a2MTBt þ a3Profitt þ a4Casht þ a5Sizet þ a6Tangt þ 1t ð3Þ

The dependent and independent variables are defined the same as in Section II. Then,I use the residual of this equation as the adjusted debt ratio.

After building the adjusted debt ratio for each firm at each year, in the second stage,I calculate the mean of adjusted debt ratio for each country at each year and then usecountry mean of adjusted debt ratio as dependent variables to run the cross-nationalregression model:

MeanAdjDebtt ¼ bX þ 1 ð4Þ

X is the vector of country-level variables.

Debt ratio

Primary ManufacturingAdvanced

manufacturing Services Pooled

MTB 20.0001 20.0000 20.0000 20.0001 * * * 20.0002 * * *

(0.80) (0.44) (0.24) (2.64) (5.07)Profit 20.0947 * * * 20.1774 * * * 20.1599 * * * 20.0807 * * * 20.0588 * * *

(13.08) (23.84) (30.59) (16.14) (12.14)Size 0.0279 * * * 0.0418 * * * 0.0279 * * * 0.0305 * * * 0.0230 * * *

(26.58) (43.64) (39.35) (51.08) (53.11)Tang 0.0955 * * * 0.1009 * * * 0.1458 * * * 0.1597 * * * 0.1557 * * *

(17.42) (17.75) (28.79) (39.03) (38.16)Constant 20.0601 * * * 20.1241 * * * 20.0685 * * * 20.0739 * * * 20.0699 * *

(10.13) (20.38) (15.40) (20.28) (2.01)No. ofobs 16,472 37,286 55,333 62,090 171,181No. offirms 2,354 4,593 6,943 8,613 22,503Adj. R 2 0.0704 0.0711 0.0602 0.0709 0.2035

Notes: Significant at: *10, * *5, * * *1 percent; absolute value of t-statistics in parentheses; the t-statistic reported in parentheses controls for firm clustering standard errors; this table presents theregression results of the following Default (with firm subscripts suppressed):

Debtt ¼ a1 þ a2MTBt þ a3Profitt þ a4Casht þ a5Sizet þ a6Tangt þ 1t

sample period is 1990-2008; the dependent variable Debt is the long-term debt ratio computed by long-term debt divided by total assets; MTB is the market-to-book ratio computed by the book value of totalassets minus the book value of equity plus the market value of equity all divided by the book value oftotal assets; Profit is computed by EBITDA divided by total assets; Size is the log of total assets in USdollars; Tang is the tangibility computed by tangible assets divided by total assets

Table V.Firm and industry factors

and financial leverage


317

The two-stage regression results are presented in Table VIII. After removing firm-levelfactors totally and controlling for sample selection bias through two-stage regression,the tests results stay statistically significant.

To address the omitting variable issue, I run the robust tests by adding additionalcountry-level controlling variables and re-run the two-stage regression. Following theprior research, I add both country-level corporate governance quality variables such asgovernment quality index and ownership concentration index and economic variables

Debt ratio(1) (2)

MTB 20.0002 * * * 20.0002 * * *

(6.28) (5.40)Profit 20.0620 * * * 20.0631 * * *

(12.78) (12.96)Size 0.0212 * * * 0.0221 * * *

(49.36) (50.79)Tang 0.1632 * * * 0.1609 * * *

(40.55) (40.06)SR 0.0586 * * *

(14.07)LR 0.0185 * * * 0.0473 * * *

(3.74) (8.90)CR 20.0167 * * * 20.0228 * * *

(24.01) (26.25)Constant 20.0445 20.0804 *

(1.16) (1.94)No. of obs 171,150 171,150Adj. R 2 0.2192 0.2240

Notes: Significant at: *10, * *5, * * *1 percent; robust t-statistics in parentheses; the t-statistic reportedin parentheses controls for firm clustering standard errors; this table presents the regression results ofthe following Default (with firm subscripts suppressed):

Debtt ¼a1 þa2MTBtþa3PROFITtþa4CASHtþa5SIZEt þa6Tangtþa7SRþa8CRþa9LRþ1t

where model (1) tests the impact of CR and LR on debt ratio and model (2) test the compounded impact ofSR, creditor right, and labor right on debt ratio; sample period is 1990-2008; the dependent variable Debtis the long-term debt ratio computed by long-term debt divided by total assets; MTB is the market-to-book ratio computed by the book value of total assets minus the book value of equity plus the marketvalue of equity all divided by the book value of total assets; Profit is computed by EBITDA divided bytotal assets; Size is the log of total assets in US dollars; Tang is the tangibility computed by tangibleassets divided by total assets; SR and CR are shareholder rights and creditor rights from Djankov et al.(2008) and Djankov et al. (2007), respectively. LR is the labor rights from Botero et al. (2004)

Table VI.Impacts of CR and LR onfinancial leverage

Variable VIF Tolerance R 2

SR 1.59 0.6306 0.3694CR 1.53 0.6515 0.3485LR 1.28 0.7826 0.2174Mean VIF 1.47

Table VII.Variance inflation factors

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such as GDP growth rate, bond market development measure, and banking sectiondevelopment measure. The regression results are reported in Table IX.

The above robust tests results show that the coefficients of major target variables:CR and LR, stay statistically significant. These significant results support thehypotheses. Specifically, LR have a positive relationship with debt ratio whereas CRhave a negative relationship with debt ratio.

V. ConclusionThis paper explores the relationship between CR as well as employee rights and capitalstructure across countries. The results reveal the impacts of bargaining powers of creditorsand employees on capital structure given a country’s legal and political framework.

MeanAdjDebtCommon law countries Civil law countries Full sample Full sample

SR 0.0421 * * * 0.0224 * * * 0.0306 * * *

(5.06) (2.83) (3.57)CR 20.0055 * * * 20.0038 * * 20.0055 * * *

(2.89) (2.12) (2.88)LR 0.0530 * * * 0.0239 * * 0.0324 * * * 0.0321 * * *

(5.96) (2.25) (2.92) (2.92)STKGDP 20.0000 20.0001 * 20.0001 *

(0.99) (1.94) (1.94)GOV_QUAL 0.0162 * * * 0.0136 * * * 0.0126 * * *

(3.70) (3.13) (2.87)ECO_GLB 0.0002 0.0005 0.0019

(0.06) (0.14) (0.55)Constant 20.0450 * * * 20.0293 * * 20.0474 * * * 20.0455 * * *

(8.01) (2.27) (3.77) (3.65)No. of obs 830 814 814 814R 2 0.0987 0.1130 0.1144 0.1244

Notes: Significant at: *10, * *5, * * *1 percent; robust t-statistics in parentheses; the t-statistic reportedin parentheses controls for county clustering standard errors; this table presents the regression resultsof the following model:

MeanAdjDebtt ¼ bX þ 1

where X is a vector of country-level variables; STKGDP, the stock market capitalization to GDP, isfrom World Bank; GOV_QUAL is the regulation quality of government, obtained from Kaufmann et al.(2007); ECO_GLB is the economic globalization index from World Bank; the dependent variable,MeanAdjDebt, is the country mean of residuals of the following model (with firm subscriptionsuppressed):


where Debt is the long-term debt ratio computed by long-term debt divided by total assets; MTB is themarket-to-book ratio computed by the book value of total assets minus the book value of equity plusthe market value of equity all divided by the book value of total assets; Profit is computed by EBITDAdivided by total assets; Size is the log of total assets in US dollars; Tang is the tangibility computed bytangible assets divided by total assets; SR and CR are shareholder rights and creditor rightsfrom Djankov et al. (2008) and Djankov and Shleifer (2007), respectively; LR is the labor rights fromBotero et al. (2004); sample period is 1990-2008

Table VIII.Country-level corporategovernance factors and

debt ratio


319

MeanAdjDebt(1) (2)

GDPG 0.0069 * * * 0.0076 * * *

(3.69) (3.96)Inflation 20.0002

(0.54)STKGDP 20.0098 * * * 20.0088 * *

(2.80) (2.27)Bond 0.0465 * * * 0.0505 * * *

(7.55) (6.90)Bank 0.0190 * * * 0.0234 * * *

(4.10) (5.03)SR 0.0431 * * * 0.0470 * * *

(3.55) (3.86)CR 20.0117 * * * 20.0119 * * *

(4.95) (5.24)LR 0.0375 * * * 0.0452 * * *

(4.14) (4.10)GOV_QUAL 20.0063

(1.05)ECO_GLB 0.0005

(0.14)Constant 20.0631 * * * 20.0714 * * *

(8.25) (4.77)Observations 746 746R 2 0.2504 0.2523

Notes: Significant at: *10, * *5, * * *1 percent; robust t-statistics in parentheses; the t-statistic reportedin parentheses controls for county clustering standard errors; this table presents the regression resultsof the following model:

MeanAdjDebtt ¼ bX þ 1

where X is a vector of country-level variables; GDPG is the GDP growth rate; Inflation is the inflationrate; Bond is the private bond capitalization to GDP; Bank is the domestic bank deposits to GDP;STKGDP, the stock market capitalization to GDP, is from World Bank; GOV_QUAL is the regulationquality of government, obtained from Kaufmann et al. (2007); ECO_GLB is the economic globalizationindex from World Bank; the dependent variable, MeanAdjDebt, is the country mean of residuals of thefollowing model (with firm subscription suppressed):


where Debt is the long-term debt ratio computed by long-term debt divided by total assets; MTB is themarket-to-book ratio computed by the book value of total assets minus the book value of equity plusthe market value of equity all divided by the book value of total assets; Profit is computed by EBITDAdivided by total assets; Size is the log of total assets in US dollars; Tang is the tangibility computed bytangible assets divided by total assets; SR and CR are shareholder rights and creditor rights fromDjankov et al. (2008) and Djankov and Shleifer (2007), respectively; LR is the labor rights fromBotero et al. (2004); sample period is 1990-2008

Table IX.Country-level economicfactors and debt ratio

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In corporate governance context, stakeholders such as shareholders, creditors, andemployees have heterogeneous utility functions. As a result, a game is played amongthose stakeholders within a country’s legal and political framework. As firm residualclaimants, shareholders stand on the one side of the game whereas other stakeholdersstand on the other side. When stakeholders other than shareholders pursue to maximizetheir benefits and interests within corporations, their gains are at the expense ofshareholders. This is the essential of interaction between stakeholders.

Using country-level CR index and LR index as a proxy for bargaining powers ofcreditors and employees, respectively, I find a positive correlation between employeerights and firms’ use of debt and a negative correlation between CR and firm debt ratio.This is because when employee rights are high, shareholders are more likely to beexploited by employees. If so, shareholders intend to use more debt obligation toremove free cash flows to reduce employees’ opportunities to obtain more benefits fromthe firm. When CR are high, creditors have more negotiation power to obtain goodterms in debt contracting, making debt less attractive to shareholders.

The empirical results are robust by controlling for sample selection bias, test modelspecification, and a series of country-level control variables. The results obtained fromthis paper helps us to understand financial leverage in different countries with variouscorporate governance mechanisms and fills significant gaps in the literature oninternational financing policy. These results should be of interest to managers,investors, and policymakers.

Notes

1. Studies on international capital structure include Aggarwal (1990), Rajan and Zingales(1995), Aivazian et al. (2001) and Gaud et al. (2007), among others.

2. I also used 1 percent winsorized sample and original sample to run all tests. The tests resultsdo not change qualitatively.

3. LLSV (2000) classify non-financial firms into seven broad industrial groups: (1) agriculture;(2) mining; (3) construction; (4) light manufacturing; (5) heavy manufacturing; (6)transportation, communications and utilities; and (7) services.

4. Since debt ratio is censored by zero at lower bound, we also use Tobit model to regress debtratio on the same firm-level independent variables, the SR, CR, and LR indices with year andindustry fixed effect. The coefficients of CR and LR stay significant statistically with theexpected sign. Since Tobit model cannot generate robust standard errors, we report ourresults based on OLS regression.

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Further reading

Beck, T., Demirguc-Kunt, A. and Levine, R. (2001), “Legal theories of financial development”,Oxford Review of Economic Policy, Vol. 17, pp. 438-501.

Beck, T., Demirguc-Kunt, A. and Levine, R. (2003), “Law, endowments, and finance”, Journal ofFinancial Economics, Vol. 70, pp. 137-82.

Blair, M. (1999), Firm-specific Human Capital and Theories of the Firm, in Employees andCorporate Governance, Brookings Institution, Washington, DC.

Blair, M. and Roe, M. (1999), Employees and Corporate Governance, Brookings Institution,Washington, DC.

Demirguc-Kunt, A. and Maksimovic, V. (1998), “Law, finance, and firm growth”, Journal ofFinance, Vol. 53, pp. 2107-37.

Demirguc-Kunt, A. and Maksimovic, V. (1999), “Institutions, financial markets and firm debtmaturity”, Journal of Financial Economics, Vol. 54, pp. 295-336.

Easterbrook, F. (1984), “Two agency cost explanations of dividends”, American EconomicReview, Vol. 74, pp. 605-59.

Grossman, S.J. and Hart, O. (1982), “Corporate financial structure and managerial incentives”, inMcCall, J. (Ed.), The Economics of Information and Uncertainty, University of ChicagoPress, Chicago, IL.


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Hansmann, H. and Kraakman, R. (2004), “The end of history for corporate law”, in Gordon, J. andRoe, M. (Eds), Convergence and Persistence in Corporate Governance, CambridgeUniversity Press, Cambridge.

Jensen, M. and Meckling, W. (1976), “Theory of the firm: managerial behavior agency costs, andownership structure”, Journal of Financial and Quantitative Analysis, Vol. 3, pp. 305-60.

La Porta, R., Lopez-de-Silanes, F., Shleifer, A. and Vishny, R.W. (1999), “Corporate ownershiparound the world”, Journal of Finance, Vol. 54, pp. 471-517.

Pagano, M. and Volpin, P. (2005), “The political economy of corporate governance”, AmericanEconomic Review, Vol. 95, pp. 1005-30.

Pagano, M. and Volpin, P. (2006), “Shareholder protection, stock market development, andpolitics”, Journal of European Economic Association, Vol. 4, pp. 315-41.

Rajan, R. and Zingales, L. (2001), “Financial systems, industrial structure, and growth”, OxfordReview of Economic Policy, Vol. 17, pp. 467-82.

Roberts, M. and Sufi, A. (2009), “Control rights and capital structure: an empirical investigation”,Journal of Finance, Vol. 64, pp. 1657-95.

Roe, M.J. (2005), Corporate Governance: Political and Legal Perspectives, Oxford University Press,Oxford.

About the authorDr Bing Yu is an Assistant Professor of Finance at the School of Business, Meredith College,Raleigh, North Carolina, USA. Bing Yu can be contacted at: [email protected]

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