Aggregate Governance Quality and Capital Structure. Abstract

Aggregate Governance Quality and Capital Structure Abstract Grounded in agency theory, this study explores how capital structure is influenced by aggregate corporate governance quality. We employ broad-based measures that encompass multiple governance factors, including boards, audit quality, charter/bylaws, director quality, executive compensation, ownership, and state of incorporation. The governance measures we utilize are the most comprehensive metrics ever constructed in the literature (encompassing 51 governance standards). Consistent with agency theory, we document a significant association between leverage and governance quality. The evidence reveals that firms with poor governance are significantly more leveraged. It appears that leverage substitutes for corporate governance in alleviating agency conflicts. We also argue that leverage helps firms raise capital by alleviating agency costs in firms with poor governance quality. Finally, we utilize empirical methods that control for potential endogeneity and find the results to be robust. JEL Classification: G32, G34 Keywords: capital structure, corporate governance, agency costs, leverage 1

Aggregate Governance Quality and Capital Structure I. Introduction The literature in capital structure began with the seminal work by Modigliani and Miller (1958) on the irrelevance of capital structure. Since then, capital structure continues to be a topic of interest in financial economics and has produced a large volume of research. Harris and Raviv (1991) offer a thorough review of the capital structure literature. Several theories have been advanced to explain capital structure decisions. One theory that has garnered strong empirical support is agency theory. Agency theory posits that capital structure is determined by agency costs, i.e. costs due to conflicts of interest. The literature in this area has been built on the early work by Fama and Miller (1972) and Jensen and Meckling (1976). Motivated by agency theory, this study is related to the agency costs as an explanation for capital structure decisions. Specifically, this paper explores the association between capital structure and corporate governance quality. Corporate governance exists to mitigate agency problems. Hence, firms with better governance quality should suffer less severe agency conflicts. Leverage has been argued to alleviate agency costs in several ways. First, one way to reduce agency conflicts is to cause managers to increase their ownership in the firm (Jensen and Meckling, 1976). By increasing the use of debt financing, effectively, displacing equity capital, firms shrink the equity base, thereby increasing the percentage of equity owned by management. Second, the use of debt increases the probability of bankruptcy and job loss. This additional risk may further motivate managers to decrease their consumption of perks and increase their efficiency (Grossman and Hart, 1982). Finally, the obligation of interest payments resulting from the use of debt helps resolve the free cash flow problem (Jensen, 1986). Because leverage is 2

related to agency costs and agency costs, in turn, are related to governance quality, we hypothesize that capital structure is influenced by corporate governance quality. To gauge corporate governance quality, we employ governance standards provided by Institutional Shareholder Services (ISS). The ISS governance standards include 51 factors encompassing eight corporate governance categories: audit, board of directors, charter/bylaws, director education, executive and director compensation, ownership, progressive practices, and state of incorporation. The ISS governance standards are the most all-inclusive data on corporate governance ever collected. Based on these governance standards, we construct two comprehensive measures of governance quality. First, similar to Brown and Caylor (2006), we create the governance score. Brown and Caylor (2006) code 51 governance factors as either 1 or 0 depending on whether the firm s governance standards are minimally acceptable. The sum of each firm s 51 binary variables represents the governance score (Gov-Score). Brown and Caylor (2006) find that firms with better governance quality as measured by the governance score are more profitable and more valuable (higher Tobin s q). Their results imply that firms with better governance quality suffer lower agency costs and, hence, exhibit better performance and higher value. Second, we utilize the ISS-score, developed by Institutional Shareholder Services (ISS). The ISS-score is distinct from Brown and Caylor s (2006) because it includes some interaction effects among various governance standards. Prior studies have examined the impact of specific governance mechanisms on capital structure decisions (Berger et al., 1997; Garvey and Hanka, 1999, Harford, Li, and Zhao, 2007; 3

Jiraporn and Gleason, 2007, Litov, 2005). 1 Insightful though these studies may be, they do not account for the quality of corporate governance in totality. This paper is the first to employ a broad set of governance mechanisms that captures aggregate quality of corporate governance. Our sample is also one of the largest and most recent among corporate governance studies (over 7,000 observations from 2001 to 2004). The empirical evidence in this study shows an inverse relationship between capital structure and governance quality. In other words, firms where corporate governance is weaker are found to be significantly more leveraged. We argue that, due to the role of debt in mitigating agency costs, higher leverage substitutes for weaker governance mechanisms. Moreover, the negative association documented in this study is consistent with the substitution hypothesis. La Porta et al. (2000) posit that firms with weak governance, in an attempt to raise capital on attractive terms, need to establish a reputation for not expropriating wealth from shareholders. One way to do so, we argue, is to carry more debt for fixed interest payments reduce what is left for expropriation; the weaker the firm s governance, the stronger the need for the reputation mechanism, and, thus, the more debt the firm should carry. Finally, it can be argued that leverage and corporate governance are endogenously determined. Using the two-stage least squares approach, which is less vulnerable to endogeneity, we find that the inverse association remains robust. The results of this study enrich the literature in several ways. First, the literature in capital structure benefits because we show that governance quality is a significant determinant of capital 1 Capital structure decisions are shown to be related to certain governance mechanisms such as executive compensation (Berger et al., 1997), corporate governance provisions (Jiraporn and Gleason, 2007; Litov, 2005), board structure (Harford, Li, and Zhao, 2007), and anti-takeover statues (Garvey and Hanka, 1999). 4

structure. 2 Second, we provide empirical support for agency theory by showing that a relationship exists between leverage and governance quality, consistent with the prediction of agency theory. Third, we contribute to the literature in corporate governance as we utilize governance measures that encompass various aspects of corporate governance and show that corporate governance a material impact on capital structure decisions. The remainder of this study is organized as follows. Section II discusses the motivation, and develops two competing hypotheses. Section III shows the sample selection procedure and discusses the relevant data. Section IV discusses the methods and displays the empirical results. Finally, Section V offers the concluding remarks. II. Motivation and Hypothesis Development. a. Motivation The finance literature is replete with studies that attempt to explain the determinants of capital structure. Several hypotheses have been advanced in the past couple of decades, for instance, the signaling hypothesis (Ross, 1977 and Leland and Pyle, 1977), the pecking order hypothesis (Myers, 1984), and agency theory (Jensen, 1986). Agency theory argues that capital structure is determined by agency costs, which arise from conflicts of interests. Motivated by agency theory, this study is related to the agency costs as an explanation of capital structure; using the newly developed governance score (Brown and Caylor, 2006), we examine how capital structure is influenced by corporate governance quality. Capital structure decisions are shown to be affected by certain governance mechanisms such executive compensation (Berger et al., 2 Two recent studies by Jiraporn and Gleason (2007), and Litov (2005) also examine the impact of corporate governance on capital structure. However, they employ only the Governance Index developed by Gompers et al. (2003) to represent corporate governance. The scope of our study is much more exhaustive as our study encompasses so many facets of corporate governance, including boards, executive compensation, audit committees, director education, executive ownership, and state of incorporation. The governance metrics we use are the most comprehensive in the literature so far. 5

1997), corporate governance provisions (Jiraporn and Gleason, 2007; Litov, 2005), board structure (Harford, Li, and Zhao, 2007), and anti-takeover statues (Garvey and Hanka, 1999). Nevertheless, our study is the first to investigate the impact of aggregate governance quality on capital structure, using the broadest metrics available in the literature. b. Capital Structure and Corporate Governance Quality Agency theory suggests that there are several ways in which debt can help mitigate agency conflicts between shareholders and managers. Holding constant the manager s absolute investment in the firm, increases in the fraction of the firm financed by debt increase the manager s share of the equity, thereby bringing the manager s and the shareholders interests into better alignment. Moreover, as argued by Jensen (1986), since debt commits the firm to pay out cash, it reduces the amount of free cash available to managers to engage in excessive perquisite consumption. Corporate governance is put in place specifically to ensure that managers act in the interest of shareholders. Therefore, corporate governance is designed to minimize agency conflicts. Because corporate governance is influenced by agency costs, and agency costs, in turn, impact capital structure decisions, we argue that a relationship should exist between leverage and corporate governance quality. It is not entirely clear, however, what the association should be between leverage and governance quality, we advance two competing hypotheses that may explain the influence of governance quality on capital structure. b.1) The Outcome Hypothesis This view argues that capital structure is determined as an outcome of corporate governance quality. Firms with low governance quality suffer more severe agency problems. 6

Managers of these firms are better able to exploit shareholders, placing their private benefits ahead of those of the shareholders. As argued by agency theory and shown by empirical evidence, debt plays a role in controlling agency costs, making it more difficult for opportunistic managers to misbehave. In firms with poor governance, managers experience less monitoring and are more likely to behave opportunistically. These managers are more likely to carry debt at a sub-optimal level because they do not want to impose additional constraints on themselves in the form of fixed interest payments or be deprived of free cash flow that they have control over. Therefore, this view predicts that poor governance quality is associated with low leverage. In other words, there is a positive relationship between governance quality and leverage. b.2) The Substitution Hypothesis This perspective contends that leverage acts as a substitute for corporate governance. Debt helps alleviate agency costs. Likewise, corporate governance is installed to mitigate agency conflicts. Thus, debt and governance play the same role and may substitute for each other. In firms with weak governance, the need for debt to act as a tool for controlling agency costs may be greater than in firms with strong governance. Hence, firms with poor governance quality should be more leveraged. There is also another rationale for the substitution hypothesis. This argument relies critically on the need for firms to raise money in the external capital markets, at least occasionally. To be able to raise external funds on attractive terms, a firm must establish a reputation for moderation in expropriating shareholders. One way to establish such a reputation is by carrying debt and making interest payments, which reduces what is left for expropriation 3. 3 A similar argument is made by La Porta et al. (2000) and Jiraporn and Ning (2006) on dividend policy and shareholder protection. 7

A reputation for good treatment of shareholders is worth the most for firms with weak corporate governance. As a result, the need for debt to establish a reputation is the greatest for such firms. By contrast, for firms where governance quality is high, the need for a reputation mechanism is weaker, and, thus, so is the need for leverage. This view, therefore, posits that, all else equal, leverage should be higher in firms with weaker governance quality. In other words, an inverse relationship should be observed. III. Sample Selection and Data a. Sample Selection The original sample includes firms reported by Institutional Shareholder Service (ISS) from 2001 to 2004. ISS collects data on governance standards for a large number of firms (2,400+ firms in 2001 and 5,000+ firms in 2004). Then, the sample is narrowed down by eliminating firms whose financial and accounting data do not exist on COMPUSTAT. Financial and utility firms are excluded because they are regulated and because their leverage cannot be interpreted in the same manner as for industrial firms. 4 The final sample consists of 7,557 firmyear observations. b. Corporate Governance Metrics To gauge corporate governance quality, we employ year-end data on governance standards provided by Institutional Shareholder Service (ISS). The scope of the governance data is very broad, encompassing fifty one governance standards in eight categories as defined by ISS. The eight categories include audit issues, board structure and composition, other charter and bylaw provisions, director education, executive and director compensation, director and officer 4 SIC codes 6000-6999 and 4900-4999 respectively. 8

ownership, progressive practices, and laws of the state of incorporation related to takeover defenses. 5 It is critical to note that the governance standards reported by ISS capture various dimensions of corporate governance. For instance, the Audit category includes four governance standards associated with auditor independence (composition of the audit committee, ratification at the annual meeting, consulting fees paid to auditors, and the company s policies on auditor rotation). The Charter category consists of seven governance standards related to provisions for delaying or impeding takeovers. The Board category is composed of seventeen governance standards related to the composition and other characteristics of the board. Finally, two categories, Director Education and State, consist of a single governance factor. We employ two metrics to gauge the aggregate quality of corporate governance. First, following Brown and Caylor (2006), we construct an index for each firm by assigning one point for each governance standard that is satisfied. We label this index Gov-score. We ascertain whether a specific governance standard is met using the minimum standard provided in the ISS Corporate Governance: Best Practices User Guide and Glossary (2003). Second, we employ the metric computed by ISS to measure governance quality. We refer to this metric as ISS-score. Although constructed based on the same governance standards, ISS-score is different from Gov-score because ISS-score allows interaction terms that occur in combination with others. For instance, ISS assigns more weight to a firm whose board consists of a majority of independent directors and whose key board panels (audit, nominating, and composition) are all composed of independent directors, than it assigns to each of those standards individually. 6 5 The fifty one governance standards and their eight categories are shown in the Appendix, which is similar to Table 1 in Brown and Caylor (2006). 6 ISS-score, converted to a relative index, is now publicly available on financial websites under the registered trademark Corporate Governance Quotient. To compute a Corporate Governance Quotient (CGQ) for each firm, 9

It is noteworthy that Gov-score and ISS-score are better than the Governance Index, developed by Gompers et al. (2003) for several reasons. 7 First, the ISS data are available for a much larger number of firms in more recent years. Second, the ISS data are available annually, rather than biannually. Third, the ISS data are much broader, and still encompass about half of the standards incorporated into the Gompers index. Finally, the ISS data include five of the six standards that are identified as most relevant for firm value (Bebchuk, Cohen, and Ferrell, 2005). C. Descriptive Statistics Table 1 summarizes the descriptive statistics for salient firm characteristics. The average debt ratio for the sample is 22.08%. On average, the sample firms have $5,113 millions in assets. The EBIT ratio averages 8.78%. Tobin s q, which proxies for growth opportunities, averages 1.46. The fixed assets ratio averages 4.75%. The ratio of non-debt tax shields to total assets averages 4.29%. 8 The average Gov-score is 22.95, ranging from 8 to 44. The ISS-score averages 56.21, ranging from 17 to 96.95. We also show summary statistics for each governance category. Board, Audit, Charter, State, Ownership, Compensation, Progressive, and Director Education denote governance score for each of the following categories: board, audit, charter/bylaws, state of incorporation, ownership, executive and director compensation, progressive practices, and director education. ISS analysts employ publicly available documents and website disclosure to gather data on sixty three different issues in the following four broad rating categories: board of directors, audit, anti-takeover, and compensation/ownership. On the basis of this information and a scoring system developed by an external advisory panel and ISS, they compute a CGQ for each company. While each variable is assessed on an individual basis, some variables are also evaluated in combination under the supposition that corporate governance is improved by the presence of selected combinations of favorable governance provisions. 7 This index has been widely employed in a large number of recent studies. For instance, the Governance Index has been related to capital structure (Jiraporn and Gleason, 2006), to the cost of debt financing (Klock, Mansi, and Maxwell, 2005), to the cost of bank loans (Chava, Dierker, and Livdan, 2005), to the cost of equity (Huang, 2005), to corporate diversification (Jiraporn, Kim, Davidson, and Singh, 2006), to debt maturity structure (Jiraporn and Kitsabunnarat, 2007), and to CEO compensation (Fahlenbrach, 2004, Jiraporn, Kim, and Davidson, 2005). 8 We define non-debt tax shields as the sum of depreciation and amortization. 10

IV. Empirical Results a. Univariate Analysis Table 2 Panel A shows the means and medians of Gov-score, ISS-score, and the debt ratio by year. The average ISS score appears to remain consistent over the years whereas Govscore exhibit an upward trend, increasing from an average of 16.08 in 2001 to 22.94 in 2004. This trend may signify a heightened awareness on corporate governance quality in more recent years. In Table 2 Panel B, we segregate the sample into four quartiles based on the debt ratio. b. Correlation Analysis c. Regression Analysis To ascertain the impact of aggregate governance quality on leverage, we perform a regression analysis, where leverage is the dependent variable. The independent variables of interest are Gov-score and ISS-score. We include control variables based on past empirical 11

research on capital structure. Numerous studies have argued that leverage may be positively affected by firm size. Following Titman and Wessels (1988) and Johnson (1997), we use the natural logarithm of sales to proxy for firm size. The composition of the firm s assets has been found to affect capital structure decisions (Titman and Wessels, 1988 and Mehran, 1992). Hence, we include the fixed assets ratio in the regression analysis. As in Johnson (1997), the fixed asset ratio is property, plant, and equipment to total assets. Myers (1977) identifies growth opportunities as a significant determinant of capital structure. Similarly, Rozeff (1982) finds empirical support for growth opportunities as a relevant variable. We control for growth opportunities by using Tobin s q. The computation of Tobin s q is based on Chung and Pruitt (1994). Profitability may be relevant to capital structure decisions. Myers (1984) suggests that managers have a pecking order in which retained earnings represent the first choice, followed by debt financing, then equity. Thus, the pecking order hypothesis would imply a negative relationship between profitability and leverage. We employ the EBIT ratio to control for profitability. DeAngelo and Masulis (1982) contend that non-debt tax deductions substitute for the tax shield benefits of debt. As a result, firm with greater non-debt tax shield would be expected to have lower levels of debt. We define non-debt tax shields as the ratio of the sum of depreciation and amortization to total assets. Finally, we include year dummies to capture leverage variation over time. The regression results are reported in Table 4. Model 1 includes the logarithm of Govscore and the control variables. 9 The coefficient for Gov-score is negative and highly significant, implying that firms with better governance adopt lower leverage. The evidence seems to be 9 Following Chung, Elder, and Kim (2007), we use the log form to reduce the potential impact of outliers. Using the raw scores produces similar results. 12

consistent with the substitution hypothesis. As leverage can function as a device for controlling agency costs, firms with better governance (hence, less agency costs) do not need leverage as much as those with poor governance. This is why there is an inverse relation between governance quality and leverage. Model 2 is similar to Model 1 except that we replace Gov-score with ISS-score. The coefficient of ISS score is negative and significant. Thus, regardless of how governance quality is measured, there is an inverse relation between leverage and governance quality, consistent with the prediction of the substitution hypothesis. D. Possible Endogeneity It can be argued that leverage and corporate governance quality may be endogenously determined. If this is the case, ordinary least squares estimates may be biased. Cognizant of possible endogeneity, we employ an alternative estimation method that explicitly takes into account potential endogeneity. We use a two-stage least squares (2SLS) analysis. 10 The 2SLS results are shown in Table 5. Note that the coefficient of Gov-score is negative and significant in Model 1. Similarly, ISS-score shows a negative and significant coefficient in Model 2. The 2SLS results support the substitution hypothesis and are thus in agreement with the OLS results reported earlier 11 Endogeneity thus does not appear to unduly affect the results. E. Relations between Leverage and Governance Categories/Standards The empirical evidence so far demonstrates a significant association between leverage and composite governance scores (Gov-score and ISS-score). To gain further insights, we 10 We use three instrumental variables. First, we use a dummy variable that is equal to one if the firm is listed on the NYSE, zero otherwise. We posit that, due to strict requirements from NYSE, governance quality of firms listed on NYSE should be higher than those not listed there. Second, we use a dummy variable that is set to one if the observation is after 2002 (after Sarbanes-Oxley was enacted), zero otherwise. We assume that governance quality should improve afer 2002 due to the numerous mandated changes imposed by Sarbanes-Oxley. Finally, we use the effective spread, which measures a stock s liquidity. There is evidence that governance quality is associated with liquidity (Chung, Elder, and Kim, 2007). 11 We also run an alternative analysis where we add firm size and profitability as instrumental variables. The results remain similar and thus appear to be robust. 13

investigate which governance standards drive the association between leverage and aggregate governance quality. Although theory does not provide clear guidance o this issue, we can make certain conjectures on which categories of Gov-score and ISS-score should have more influence on leverage. For instance, as detailed in the Appendix, two categories of Gov-score, State and Director education, consist of just a single governance standard. For most firms, these governance standards are not met. For State, the single governance standard is whether the firm is incorporated in a state without any anti-takeover provisions. In 2004, fewer than 4% of firms satisfied this standard. Likewise, in 2004, fewer than 2% of firms satisfied the single governance standard under Director education. These governance categories are therefore unlikely to explain much variation in leverage. To ascertain which governance categories drive the results, we run a regression analysis, where leverage is regressed on the eight governance standards shown in the Appendix (the eight standards are Board, Audit, Charter, State, Ownership, Compensation, Progressive, and Director education) and the control variables. The regression results are shown in Table 6. We find that five governance categories are negatively associated with leverage; Board, Ownership, Audit, State, and Compensation. 12 It is worth noting that the coefficient of Charter is not significant. This is somewhat unexpected because Charter is the category that is most closely related to the Governance Index developed by Gompers et al. (2003). Each of the seven standards in Charter also appear in the Governance Index. The results are surprising, given that both Litov (2005) and Jiraporn and Gleason (2007) report a significant association between leverage and the Governance Index. 12 We do not include all the governance categories in a single regression due to multi-collinearity. Nevertheless, when all of them are included, their coefficients generally retain the signs and significance levels except for Compensation. 14

V. Concluding Remarks We relate capital structure to aggregate corporate governance quality. Agency theory argues that capital structure decisions are influenced by agency costs. Corporate governance is designed to alleviate agency problems. We argue that capital structure and corporate governance are related through their association with agency costs. Two hypotheses are advanced to explain the relationship; the outcome hypothesis and the substitution hypothesis. Employing broad-based comprehensive governance indices, we empirically test the link between leverage and governance quality. The empirical evidence demonstrates an inverse relation, which is consistent with the prediction of the substitution hypothesis. There are two 15

reasons why there is a substitution effect. First, both leverage and corporate governance function as mechanisms for controlling agency costs. One mechanism may substitute for the other, thus a negative association between the two. Second, leverage may help firms raise capital with more ease. To be able to raise external funds on reasonable terms, firms need to establish a reputation for not exploiting shareholders. Leverage offers a monitoring role that reduces management s ability to take advantage of shareholders. A reputation for favorable treatment of shareholders is worth the most in firms with poor governance quality. Therefore, leverage is more necessary in such firms. This is why firms with low governance quality are more leveraged. 16

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- Jiraporn, P., and K. Gleason, 2007, Capital structure, shareholder rights, and corporate governance, Journal of Financial Research, forthcoming. - Johnson, S. A., 1997, The effect of bank debt on optimal capital structure, Financial Management 28, 47-56. - La Porta, Rafael, Florencio, Lopez- De Salinas, Andrei Shleifer, and Robert Vishny, 2000, Agency problems and dividend policy around the world, Journal of Finance 55, 1-33. - Leland, Hayne and David Pyle, 1977, Information asymmetries, financial structure, and financial intermediation, Journal of Finance 32, 371-388. - Litov, L.P., 2005, Corporate governance and financing policy: New evidence, Working paper, Washington University, St. Louis. - Mehran, H., 1992, Executive incentive plans, corporate control, and capital structure, Journal of Financial and Quantitative Analysis 27, 539-560. - Modigliani, F. and M. Miller, 1958, The cost of capital, corporation finance, and the theory of investment, American Economic Review 48, 261-297. - Morck, R., A. Shleifer, and R. Vishney, 1988, Management Ownership and Market Valuation: An Empirical Analysis, Journal of Financial Economics 20: 293-316. - Myers, S., 1977, Determinants of corporate borrowing, Journal of Financial Economics 5, 147-176. - Myers, S., 1984, The capital structure puzzle, Journal of Finance 39, 575-592. - Ross, Stephen, 1977, The determination of financial structure: The incentive signaling approach, Bell Journal of Economics 8, 23-40. - Rozeff, M., 1982, Growth, beta and agency costs as determinants of dividend payout ratios, Journal of Financial Research 5, 249-259. - Schooley, D. and D. Barney, 1994, Using dividend policy and managerial ownership to reduce agency costs, Journal of Financial Research 17, 363-373. - Titman, S. and R. Wessels, 1988, The determinants of capital structure choice, Journal of Finance 43, 1-19. 18

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Table 1. Descriptive statistics We create an index for each firm by awarding one point for each governance standard that is met, and denote this index Gov-score. We determine whether a particular governance standard is met using the minimum standard provided in ISS Corporate Governance: Best Practices User Guide and Glossary (2003). ISS-score is the governance index provided by Institutional Shareholder Service (ISS). Board, Audit, Charter, State, Ownership, Compensation, Progressive, and Director Education denote governance score for each of the following categories: board, audit, charter/bylaws, state of incorporation, ownership, executive and director compensation, progressive practices, and director education. Percentile Variable Mean Standard deviation Min 25 50 75 Max Debt ratio 22.08 19.80 0 4.30 18.96 33.91 99.95 Total assets 5112.69 26705 1.665 171.23 663.54 2426.20 1009569 EBIT ratio 8.78 28.05-900.91 2.94 8.81 17.86 97.09 Tobin s q 1.46 1.89-0.59 0.67 1.06 1.67 67.29 Fixed asset ratio 4.75 5.97-3.20 1.41 3.08 5.92 109.53 Non-debt tax shields 4.29 4.80 0.00 1.88 3.58 5.54 153.55 MTRBE 29.65 10.48 0.00 30.40 35.00 35.01 39.49 MTRAF 20.54 15.27 0.00 2.55 28.98 35.00 39.49 Gov-score 22.95 6.41 8.00 18.00 22.00 28.00 44.00 ISS-score 56.21 12.84 17.00 46.68 56.40 65.60 96.95 Board 9.18 2.79 2.00 7.00 9.00 11.00 17.00 Ownership 1.90 0.83 0.00 1.00 2.00 2.00 4.00 Charter 2.35 1.43 0.00 1.00 2.00 3.00 6.00 Audit 2.02 1.18 0.00 1.00 2.00 3.00 4.00 State 0.03 0.18 0.00 0.00 0.00 0.00 1.00 Compensation 6.05 1.27 2.00 5.00 6.00 7.00 10.00 Progressive 1.42 1.97 0.00 0.00 0.00 2.00 7.00 Director education 0.01 0.10 0.00 0.00 0.00 0.00 1.00 20

Table 2: Univariate Analysis Panel A. ISS Score, Gov-score, and Debt Ratio by year Year Sample Mean (Median) 2001 1487 2002 1707 2003 3046 2004 2981 ALL 9221 Panel B. ISS Score, Gov-score, and Debt Ratio by quartile ISS Score Gov-Score Debt Ratio 53.86 (54.40) 58.23 (58.85) 51.44 (50.50) 61.09 (62.10) 56.21 (56.40) Quartile Sample Mean (Median) 1 st quartile 2306 39.55 (40.60) 2 nd quartile 2305 51.74 (51.80) 3 rd quartile 2305 61.01 (61.00) 4 th quartile 2305 72.60 (71.40) ALL 9221 56.21 (56.40) *, **, *** statistically significant at the 10%, 5%, and 1% level respectively. Mean (Median) 16.08 (16.00) 17.74 (17.00) 23.91 (23.00) 28.09 (28.00) 22.94 (22.00) Mean (Median) 0.2389 (0.2175) 0.2381 (0.2195) 0.2138 (0.1801) 0.2088 (0.1729) 0.2207 (0.1895) ISS Score Gov-Score Debt Ratio Mean (Median) 18.55 (19.00) 20.89 (22.00) 23.30 (25.00) 29.04 (31.00) 22.94 (22.00) Mean (Median) 0.2143 (0.1582) 0.2097 (0.1728) 0.2212 (0.1944) 0.2375 (0.2229) 0.2207 (0.1895) 21

Table 3. Correlation matrix Debt Govscore ISS LNTA EBITR Q FIXAR NDTSR Board Owner Charter Audit State Comp Progress Diredu Debt 1.000 Gov-score 0.042 1.000 0.000 ISS score 0.017 0.583 1.000 0.103 0.000 LNTA 0.295 0.365 0.139 1.000 0.000 0.000 0.000 Ebitr 0.125 0.117 0.066 0.312 1.000 0.000 0.000 0.000 0.000 Q -0.145-0.027 0.005-0.257-0.104 1.000 0.000 0.007 0.601 0.000 0.000 FIXAR 0.001-0.014-0.078-0.015-0.004 0.065 1.000 0.960 0.205 0.000 0.150 0.713 0.000 NDTSR 0.007-0.080-0.097-0.162-0.397 0.073 0.348 1.000 0.543 0.000 0.000 0.000 0.000 0.000 0.000 Board -0.010 0.593 0.901 0.112 0.053 0.020-0.058-0.080 1.000 0.342 0.000 0.000 0.000 0.000 0.051 0.000 0.000 Ownership 0.056 0.506 0.402 0.356 0.082-0.055-0.038-0.063 0.293 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Charter -0.019 0.043 0.224-0.142-0.041 0.029-0.031 0.027 0.056-0.150 1.000 0.066 0.000 0.000 0.000 0.000 0.004 0.004 0.010 0.000 0.000 Audit -0.032 0.256 0.740-0.076 0.012 0.049-0.069-0.076 0.666 0.129 0.017 1.000 0.003 0.000 0.000 0.000 0.247 0.000 0.000 0.000 0.000 0.000 0.083 State -0.059 0.092 0.091-0.059 0.006 0.010 0.012-0.006 0.084-0.030 0.122 0.042 1.000 0.000 0.000 0.000 0.000 0.577 0.348 0.267 0.569 0.000 0.003 0.000 0.000 Compensation 0.086 0.348 0.612 0.177 0.101-0.043-0.041-0.093 0.433 0.262-0.021 0.398-0.015 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.040 0.000 0.133 Progressive 0.065 0.502 0.756 0.322 0.082-0.027-0.036-0.068 0.661 0.415-0.068 0.482-0.016 0.407 1.000 0.000 0.000 0.000 0.000 0.000 0.008 0.001 0.000 0.000 0.000 0.000 0.000 0.101 0.000 Dir. education 0.024 0.110 0.146 0.056 0.015-0.006 0.002 0.000 0.131 0.109-0.015 0.101-0.018 0.082 0.158 1.000 0.022 0.000 0.000 0.000 0.144 0.533 0.888 0.983 0.000 0.000 0.126 0.000 0.071 0.000 0.000 22

Table 4. Regression results for governance indices This table shows the results of the following regression model: Debr ratio i,t = β 0 + β 1 Log(Gov- score i,t or ISS-score i,t ) + β 2 Log(Total-assets) i,t + β 3 EBIT i,t + β 4 Tobin s q i,t + β 5 Fixed asset ratio i,t + β 6 Non-debt tax shield i,t + Year dummies + ε i,t ; Intercept 0.1973*** (4.16) Model 1 Model 2 0.3106*** (5.66) Log(Gov-score) -0.0644*** (-3.39) Log(ISS-score) -0.0739*** (-4.97) Log(Total-assets) 0.0284*** (13.57) EBIT ratio 0.0676*** (3.54) Tobin s q -0.0104*** (-3.39) Fixed asset ratio 0.1842*** (2.88) Non-debt tax shield 0.1667** (2.03) Year 2002 0.0003 (0.07) Year 2003 0.0411*** (4.07) Year 2004 0.0384*** (3.00) 0.0287*** (14.45) 0.0702*** (3.65) -0.0102*** (-3.34) 0.1878*** (2.96) 0.1606** (1.98) -0.0018 (-0.43) 0.0101** (2.09) 0.0102* (1.74) Adjusted R 2 11.47% 11.82% F-statistics 109.40*** 113.53*** # of observations 7,531 7,557 *, **, *** statistically significant at the 10%, 5%, and 1% level respectively. 23

Table 5. Robustness Regression results for governance indices This table shows the results of the following regression model: Debr ratio i,t = β 0 + β 1 Log(Gov- score i,t or ISS-score i,t ) + β 2 Log(Total-assets) i,t + β 3 EBIT i,t + β 4 Tobin s q i,t + β 5 Fixed asset ratio i,t + β 6 Non-debt tax shield i,t + Year dummies + ε i,t ; Model 1 Model 2 Instrumental Method Instrumental Method Intercept 3.4068*** 9.4683*** (13.41) (24.19) Predicted Log(Gov-score) Predicted Log(ISS-score) -1.3484*** (-13.29) Log(Total-assets) 0.0864*** (17.17) EBIT ratio 0.0506*** (2.81) Tobin s q -0.0089*** (-2.75) Fixed asset ratio 0.1648*** (2.73) Non-debt tax shield 0.1463* (1.75) Year 2002-0.0005 (-0.13) Year 2003 0.6396*** (13.38) Year 2004 0.6353*** (13.11) -2.5626*** (-24.22) 0.1449*** (27.90) 0.0653*** (3.92) -0.0042 (-1.14) 0.1619*** (3.00) 0.0088 (0.10) 0.0050 (1.52) 0.1015*** (17.46) 0.1066*** (16.74) Adjusted R 2 17.47% 34.23% F-statistics 59.32*** 117.97*** # of observations 7,557 7,557 *, **, *** statistically significant at the 10%, 5%, and 1% level respectively. 24

Table 6. Regression results for governance quality indices Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Intercept 0.0658*** (4.21) 0.0459*** (3.11) 0.0352** (2.18) 0.0413*** (2.80) 0.0419*** (2.83) 0.0330* (1.95) 0.0183 (1.10) Board -0.0070*** (-4.23) Ownership -0.0135*** (-3.33) Charter 0.0016 (0.71) Audit -0.0065* (-1.67) State -0.0519*** (-2.85) Compensation 0.0019 (0.71) Progressive -0.0070*** (-3.65) Director education Log(Total-assets) 0.0283*** 0.0277*** 0.0255*** 0.0258*** 0.0251*** 0.0250*** 0.0286*** (14.33) (13.68) (14.06) (14.19) (14.00) (13.26) (13.38) EBIT ratio 0.0673*** 0.0673*** 0.0686*** 0.0681*** 0.0689*** 0.0685*** 0.0674*** (3.53) (3.56) (3.58) (3.54) (3.60) (3.56) (3.55) Tobin s q -0.0103*** -0.0105*** -0.0107*** -0.0106*** -0.0107*** -0.0107*** -0.0105*** (-3.35) (-3.35) (-3.39) (-3.40) (-3.42) (-3.40) (-3.38) Fixed asset ratio 0.1856*** 0.1842*** 0.1892*** 0.1866*** 0.1910*** 0.1872*** 0.1874*** Non-debt tax shield Year 2002 Year 2003 Year 2004 (2.92) 0.1660** (2.02) -0.0042 (-1.03) 0.0378*** (4.77) 0.0360*** (3.54) (2.86) 0.1699** (2.08) -0.0021 (-0.50) 0.0179*** (3.41) 0.0067 (1.18) (3.02) 0.1684** (2.06) -0.0056 (-1.36) 0.0128*** (2.59) 0.0001 (0.03) (2.96) 0.1684** (2.06) -0.0053 (-1.29) 0.0248*** (2.93) 0.0149 (1.51) (3.05) 0.1670** (2.04) -0.0039 (-0.95) 0.0145*** (2.94) 0.0019 (0.36) (2.98) 0.1697** (2.07) -0.0065 (-1.45) 0.0099 (1.37) -0.0026 (-0.36) (2.99) 0.1729** (2.11) -0.0041 (-1.00) 0.0227*** (3.83) 0.0233*** (2.65) 0.0402*** (2.71) 0.0162 (0.75) 0.0253*** (14.10) 0.0687*** (3.58) -0.0107*** (-3.40) 0.1883*** (2.99) 0.1682** (2.06) -0.0053 (-1.29) 0.0130*** (2.62) 0.0001 (0.01) R 2 11.72% 11.57% 11.28% 11.32% 11.47% 11.28% 11.51% 11.27% # observations 7,531 7,531 7,531 7,531 7,531 7,531 7,531 7,531 25

Appendix: Governance Standards Included in the Construction of the Governance Score Governance Standards A. Audit 1. Audit committee consists solely of independent outside directors 2. Auditors were ratified at the most recent annual meeting. 3. Consulting fees paid to auditors are less than audit fees paid to auditors 4. Company has a formal policy on auditor rotation B. Board of Directors 1. Managers respond to shareholder proposals within 12 months of shareholder meeting 2. CEO serves on no more than two additional boards of other public companies. 3. All directors attend at least 75% of board meetings or had a valid excuse for non-attendance. 4. Size of board of directors is at least 6 but not more than 15 members. 5. No former CEO serves on board. 6. CEO is not listed as having a related party transaction in proxy statement. 7. Board is controlled by more than 50% independent outside directors. 8. Compensation committee is comprised solely of independent outside directors. 9. The CEO and chairman duties are separated or a lead director is specified. 10. Shareholders vote on directors selected to fill vacancies. 11. Board members are elected annually. 12. Shareholder approval is required to change board size. 13. Nominating committee is comprised solely of independent directors. 14. Shareholders have cumulative voting rights to elect directors. 15. Board guidelines are in each proxy statement. 16. Policy exists requiring outside directors to serve on no more than five additional boards. C. Charter/Bylaws 1. A simple majority vote is required to approve a merger (not a supermajority). 2. Company either has no poison pill or a pill that was shareholder approved. 3. Shareholders are allowed to call special meetings. 4. A majority vote is required to amend charter/bylaws (not a supermajority). 5. Shareholders may act by written consent and the consent is non-unanimous. 6. Company is not authorized to issue blank check preferred stock. 7. Board cannot amend bylaws without shareholder approval or can only do so under limited circumstances. D. Director Education

1. At least one member of the board has participated in an ISS-accredited director education program. E. Executive and Director Compensation 1. No interlocks exist among directors on the compensation committee. 2. Non-employees do not participate in company pension plans. 3. Option re-pricing did not occur within last three years. 4. Stock incentive plans were adopted with shareholder approval. 5. Directors receive all or a portion of their fees in stock. 6. Company does not provide any loans to executives for exercising options. 7. The last time shareholders voted on a pay plan, ISS did not deem its cost to be excessive. 8. The average options granted in the past three years as a percentage of basic shares outstanding did not exceed 3% (option burn rate). 9. Option re-pricing is prohibited. 10. Company expenses stock options. F. Ownership 1. All directors with more than one year of service own stock. 2. Officers and directors stock ownership is at least 1% but not over 30% of total shares outstanding. 3. Executives are subject to stock ownership guidelines. 4. Directors are subject to stock ownership guidelines. G. Progressive Practices 1. Mandatory retirement age for directors exists. 2. Performance of the board is reviewed regularly. 3. A board-approved CEO succession plan is in place. 4. Board has outside advisors. 5. Directors are required to submit their resignation upon a change in job status. 6. Outside directors meet without the CEO and disclose the number of times they met. 7. Directors term limits exist. H. State of Incorporation 1. Incorporation in a state without any anti-takeover provisions. 27