• No results found

Founding Family Ownership and the Agency Cost of Debt


Academic year: 2021

Share "Founding Family Ownership and the Agency Cost of Debt"


Loading.... (view fulltext now)

Full text


Founding Family Ownership and the Agency Cost of Debt

August 28, 2001

Ronald C. Andersona, Sattar A. Mansib, and David M. Reeba

aKogod School of Business

Assistant Professor and Kogod Faculty Research Fellow American University

4400 Massachusetts Ave, NW Washington, DC 20016

randers@american.edu bRawls School of Business Assistant Professor of Finance

Texas Tech University Area of Finance, Box 42101

Lubbock, TX 79409-2101 smansi@ba.ttu.edu acorrosponding Author: Kogod School of Business

Assistant Professor and Kogod Faculty Research Fellow American University

4400 Massachusetts Ave, NW Washington, DC 20016

(202) 885-1940 reeb@american.edu

We are grateful to Theodore Barnhill of the Financial Markets Research Institute at the George Washington University for providing firm debt data. All remaining errors are the sole responsibility of the authors.


Founding Family Ownership and the Agency Cost of Debt


We investigate the impact of founding family ownership on the agency costs of debt in a sample of large publicly traded firms. We find that founding family ownership is associated with a significantly lower cost of debt financing and higher excess bondholder value. In addition, we find that board independence is associated with a lower cost of debt financing, but that large independent blockholders have little impact on debt yields. Further testing indicates that when family members serve as the firm’s CEO, the cost of debt financing is higher than if an outsider is a CEO, but still lower than in non-family firms. In aggregate, the results suggest that continued founding family ownership in publicly traded firms reduces the agency costs of debt.

JEL Classification: G3

Key Words: Ownership Structure, Agency Costs of Debt, Corporate Governance, Bondholder Value


1. Introduction

Jensen and Meckling (1976) observe that diversified shareholders have incentives to expropriate bondholder wealth by investing in risky, high-expected return projects (asset substitution). Debtholders, anticipating such incentives, demand higher rents, which results in a higher cost of debt capital. However, shareholders with large undiversified ownership stakes may have very different incentive structures relative to atomistic shareholders (e.g., Shleifer and Vishny (1997)). Because concentrated equity holders often have substantial portions of their wealth at risk, are typically long-term investors, and because firms regularly reenter debt markets for financing, these claimants have a strong impetus to mitigate agency conflicts with bondholders.

We explore the role of equity ownership structure in the conflicts of interest between shareholders and bondholders (i.e., the agency cost of debt). We focus on an unusual but prevalent form of ownership in public firms comprising a relatively homogenous group of investors, founding families. These families are an important element in many publicly traded firms. Among the S&P-500 firms for example, one third have continued founding family ownership, with families on average holding about 18% of the firm’s shares.1 As the typical firm in the S&P-500 is over 90 years old, continued family ownership represents a long-term commitment and provides an unusual position to influence the firm.2 We posit that founding families are a unique class of shareholders because they typically hold undiversified portfolios, show concern over firm and family reputation, and often pass their holdings on to future generations. As such, we anticipate that family ownership reduces agency conflicts with debtors; suggesting that one-time bondholder expropriation is not a desirable action. More specifically, we posit that family ownership in public firms is associated with a lower cost of debt financing (i.e., a lower yield spread3).

While family ownership in itself potentially mitigates agency conflicts, families can also exert further influence by placing one of their members in the position of CEO. If families act to reduce the cost of debt, we also expect that family firms with family CEOs to experience an incremental reduction in the cost of debt relative to non-family firms. Therefore, we also investigate whether founder CEOs, other family members, or outside managers influence the cost of debt financing. Finally, we examine two independent firm monitors (directors and outside blockholders) that are strong advocates for firm health and stability to test the robustness of our results. Because

1 Gersick, Davis, Hampton, and Lansberg (1997) estimate that family firms account for 65% to 80% of all businesses. 2 Family firms include both firms with non-family members as CEO as well as firms with a family member as CEO. Further details concerning family ownership among the S&P 500 firms is provided in section 3.


shareholders can benefit from a lower long-term cost of debt, independent directors and unaffiliated blockholders potentially have incentives to protect bondholder interests.

Using a sample of 252 industrial firms in the Lehman Brothers Index and the S&P-500, we find evidence that family ownership is associated with a lower cost of debt financing. After controlling for industry and firm specific characteristics, our analysis indicates the cost of debt for family firms is about 40 basis points lower than in non-family firms. We also find that excess bondholder value is approximately 18% greater for family versus non-family firms. Our results also indicate that the gains in debt financing are not uniform over the entire range of family ownership. Specifically, the greatest gains accrue to those firms with 1 to 12 percent family ownership.4 Overall, our investigation suggests that bond investors view founding-family ownership as an organizational structure that better protects their interests. The results are both statistically and economically significant.

Contrary to our prediction on CEO status, we document that family CEOs are associated with a higher cost of debt financing. Our results indicate, however, that higher debt costs are primarily attributable to founder descendants and that after controlling for CEO type, family firms continue to experience a significantly lower costs of debt financing. Finally, we find that independent directors are associated with substantially lower debt yields, while other outside blockholdings do not have an impact on the cost of debt. One interpretation is that institutional investors represent the holdings of a well-diversified stockholder (e.g., Fidelity Investments), while family ownership represents a committed and an undiversified blockholder with strong incentives to monitor the firm.

Our research contributes to the literature in four important ways. First, we document that family ownership impacts the cost of debt financing, providing the first evidence that equity ownership structure influences the cost of debt.5 Second, our analysis suggests that large blockholders have varying incentive structures. Institutional investors, such as mutual funds and insurance companies, have a significantly different effect on the cost of debt financing than family

4 Specifically, we find that family firms with ownership levels between 1 to 12 percent enjoy about a 50 basis point reduction in the cost of debt financing, while firms with greater than 12% ownership have about a 22 basis point reduction in the cost of debt (all relative to non-family firms). This issue is explored in detail in section 4.

5 The only related work is that of Bagnani et al. (1994), who explore the effect of CEO ownership on bond holding period returns (HPRs) primarily due to limited data. HPRs are a function of interest rate variability since they are based on the annual change in bond prices. Elton and Gruber (1995) note that holding period returns bear little resemblance to the cost of debt financing, and that corporate decision making or capital budgeting is typically described in terms of the cost of debt financing (i.e., yield to maturity in computing the weighted average cost of capital). We base our analysis using yield spreads and explore the impact of family ownership, other blockholders, outside directors, and CEO affiliation on the costs of debt financing.


blockholders. Third, we provide direct cross-sectional evidence that board independence is associated with lower debt costs and greater bondholder values. In fact, this is one of the first cross-sectional studies suggesting that independent directors are associated with a lower cost of debt financing and therefore have a positive impact on firm performance.6 Finally, prior literature is divided on which party, stockholders or bondholders, bears the agency costs of debt. Jensen and Meckling (1976) suggest that equity holders bear this cost, while Barnea, Haugen and Senbet (1981) suggests that bondholders bear the cost. Our analysis, at least in relation to family firms, suggests that these costs are born by equity claimants through higher debt financing costs.

The remainder of this paper is organized as follows. Section two briefly reviews the related literature and presents our hypotheses. In section three we describe our sample, data, and variable measures. Section four describes the research design and presents the empirical results. In section five, we test the robustness of our results using alternative measures and specifications. Section six provides a summary and conclusion.

2. Family Firms and the Agency Cost of Debt

2.1. Agency Costs of Debt

The agency costs of debt are typically described in terms of the asset substitution or the risk-shifting problem.7 The potential conflict between equity and debt claimants is such that shareholders expropriate wealth from bondholders by investing in new projects that are riskier than those presently held in the firm’s portfolio. Under this scenario, shareholders capture most of the gains (i.e., when high-risk projects payoff), while debt holders bear most of the cost (e.g., Jensen and Meckling (1976), and Fama and Miller (1972)). Alternatively, the potential conflict between security claimants may be examined in an option-pricing framework. Equity holding, or the call option, is only exercised in those states where asset value is greater than the value of the debt claim. As firm risk increases, the option becomes more valuable causing the value of the debt claim to decline.

Due to the shareholder-incentive problem arising from outside debt, bondholders typically insist on protective covenants and monitoring devices to protect themselves from risk shifting. The costs of writing and enforcing such contracts, as well as contracting for all future contingencies are,

6 Byrd and Hickman (1992) and Weisbach (1988) find evidence that outside directors have a positive impact on firm performance. Most other studies that find significant effects for outside directors, however, use event study methodology.

7 Other aspects of the agency costs of debt include liquidating dividends and the rejection of positive NPV projects in which the proceeds would accrue primarily to bondholders (see Myers (1977)).


however, not trivial. For example, covenants that deal with additional financing, dividend or lease restrictions, and mergers engender the level of complexity that bondholders can potentially protect themselves against using contractual arrangements. However, attempts to restrict future investments, while numerous, are difficult to enforce or monitor (i.e., accepting negative NPV projects). The result is that debtholders charge a higher risk premium in those cases where the agency costs of debt are higher to compensate themselves for bearing this additional risk. As such, any costs arising from the conflicts of interests between shareholders and bondholders leads to higher debt costs.

2.2. Family Firms

Large public firms are often characterized as having dispersed ownership, atomistic shareholders, and a separation between ownership and control (e.g., Demsetz and Lehn (1985)). While the potential for conflicts of interest among shareholders, debtholders, and managers are well recognized in the literature (e.g., Berle and Means (1932)), the presence of large undiversified shareholders may alleviate some of these potential conflicts as shareholders are concerned more with the long-term performance of the firm.8 Shleifer and Vishny (1997) note that concentrated holdings are common and suggest that investors prefer to bear diversification costs rather than relinquish control of the firm. Yet, costs potentially arise with concentrated equity holdings that are not present in firms with diffuse ownership. These costs can take many forms including expropriating wealth from small shareholders in the form of special dividends, excessive compensation packages, and risk avoidance.9

We investigate a class of large shareholders that potentially have unique incentive structures and a strong voice in the firm. Specifically, we focus on founding families and argue they represent poorly diversified, risk-averse investors that have powerful incentives to manage one particular firm. Casson (2001) and Chami (1999) suggest, based on Becker’s (1974,1981) familial nepotism proposition, that founding families view their firms as an asset to pass to family members or their descendants rather than wealth to consume during their lifetimes.10 As such, their firms experience

8 Tufano (1996) notes however that not all-large shareholders have undiversified portfolios. Institutional investors often have large shareholdings in multiple firms (e.g., Fidelity Investments Group) suggesting they may not be strong monitors of management but rather seek high return/risky projects similar to atomistic owners. Similarly, Woidtke (2001) explores the differing incentive structures of public versus private institutional investors.

9 In perhaps the worst form of expropriation, large shareholders remain active in the firm long after they are neither qualified nor capable of managing the company. In fact, Mueller and Inderst (2001) show theoretically how concentrated equity ownership could be associated with a higher agency cost of debt..

10 Given the wealth levels of the families with large ownership stakes in the S&P 500 firms, this attitude is much easier to comprehend.


fewer agency problems than non-family firms. Moreover, these same motives suggest that founding families have substantially longer investment time-horizons than small, diversified shareholders thereby making families long-term advocates of value maximization.

Other factors that typically ascribed to the firm’s managers also motivate families to protect and enhance firm value. These include reputation effects, competitive labor markets, and the market for corporate control. Fama (1980), for example, argues that CEOs seek to enhance or protect their reputations in the labor market.11 Similarly, we propose that concerns over reputation create motives for families to work in the interests of all shareholders. Consequently, if these additional family and market forces create adequate incentives for families to promote firm value and reduce agency costs, we anticipate debt yield spreads to be lower in family firms than in non-family firms.

Alternatively, rather than promoting firm value, families can potentially exacerbate agency conflicts because they possess the voice as well as the power to force the firm to meet their demands. Antidotal accounts in the popular press commonly imply that families expropriate wealth from the firm’s other constituents. A recent recapitalization at Ford Motor Company, for example, increased the voting power of the Ford family’s special stock, which led to widespread criticism that company’s board of directors structured a plan to benefit the Family at the expense of other claimants. If family ownership increases agency conflicts, then we expect bondholders to require higher yields from family firms.

2.3. Research Focus

Our central research question is the effect of equity ownership structure on the agency cost of debt. Since founding families arguably have similar incentive structures, they provide a clean and powerful test of whether firm ownership influences debt costs. To this end, we address two specific questions. First, do family firms enjoy lower costs of debt financing relative to non-family firms?, and second, does the level or type of family participation in the firm further impact the cost of debt financing? After controlling for other factors affecting debt costs, we posit that founding-family incentive structures reduce agency conflicts between equity claimants and bondholders causing debt yield spreads to decrease. This study provides a comprehensive empirical analysis on this subject, using firm-level data on publicly traded non-provisional debt.

11 Others have shown how these reputational concerns are positively related to the horizon of the manager (e.g., Gibbons and Murphy (1992)). Holmstrom and Costa (1986) show how the concern for reputation can lead to divergences in interest between managers and shareholders.


3. Data Description

3.1. The Sample

For our sample, we collect information on firms that are in both the Lehman Brothers Bond Database (LBBD) and the S&P-500 Industrial Index. The Lehman Brothers Bond Database provides month-end security specific information on corporate bonds, such as market value, coupon, yield, credit ratings from S&P and Moodys, duration, and maturity on nonconvertible bonds. Lehman Brothers bases their criteria for inclusion in the database on firm size, liquidity, credit ratings, subordination, and maturity. The database contains non-provisional bonds of differing maturities, differing credit ratings, and differing debt claims (senior and subordinated debt). The database’s goal is to provide a representative sample of outstanding, publicly traded debt. While the database does not contain the universe of traded debt, we have no reason to suspect any systematic bias within the sample.

We manually collect data on family ownership from proxy statements. The literature provides no commonly accepted measure or criterion for identifying a family firm. As such, we collect data on the fractional equity ownership of the founding family. For some firms, the process is straightforward since the proxy statement denotes the founder, his/her immediate family members, and their holdings. However, several generations after the founder, the family typically expands to include distant relatives or in-laws with different last names. We resolve descendent issues by manually examining corporate histories for each firm in the sample. Histories are from Gale Business Resources, Hoovers, and from company press releases and literature.12

We use the Compustat Industrial Files to garner any firm specific financial information not already included in the Lehman Brothers Database or from information in annual corporate proxy statements. Because we manually collect data on family ownership, we limit the sample from the LBBD database to firms in the S&P 500 Industrial Index. This yields 1,052 firm-year observations on 252 firms for the period 1993 through 1998.13 Descriptive statistics on the variables used in the

12 We have attempted to capture all family firms and their equity holdings. However, U.S. reporting requirements may cause a downward bias in our estimates of family ownership. This creates a bias toward zero in our testing and also suggests that a binary variable approach may be more robust.

13 To see how representative a sample based on the LBBD Indices data performs, we also collected data on the remaining 151 industrial firms on the S&P 500 (as of 1992). We find that (in the complete S&P data) the percentage of family firms is about 33.2%, the average firm size is $8.55, and leverage is 18.4%. Comparing this to our data indicates our sample is comprised of the larger firms in the S&P 500 and that as firm size decreases, family ownership is more common.


analysis are presented in section 3.4 below.

3.2. Measuring Family Ownership and the Cost of Debt Financing

A potential concern with using family ownership data is that some families are able to exert control with 2% fractional ownership, while others require 8% for the same level of control due to differences in firm size, industry, business practices, and product placement. As such, we denote family firms using a binary variable that equals 1.0 when the family holds at least 1% of the firm and 0 otherwise. Additional cutoff points are examined in section 5 of the multivariate analysis.

The cost of debt financing is measured using the yield spread (Spread), or the difference between the weighted average yield to maturity on the firm’s outstanding traded debt and yield to maturity on a Treasury security with corresponding duration. This measure is commonly used in the fixed income literature and intuitively measures the debt risk premium (e.g., Duffie (1998)). The yield on a corporate debt security is defined as the discount rate that equates the present value of the future cash flows to the security price. The yields on Treasury securities are taken from the constant maturity series published by the Federal Reserve Bank of New York in its H15 release. In the cases where there is no equivalent Treasury maturity, the yield is computed using interpolation based on the Nelson and Siegel (1987) functional form.

3.3. Control Variable Measures

We include various control variables in the analysis that potentially affect the yield spread. Firm size is measured as the natural log of the total assets of the firm. That is


(Debt Equity


Size= + (1)

where Debt is the sum of the firms traded (market value) and non-traded (book value) debt, and Equity is the market capitalization of the firm. The market value of debt is computed by multiplying the face value of the outstanding debt by its trading debt price (as a percentage of par), while the market value of equity is computed by multiplying the number of shares outstanding by the trading stock price.14

14 Our results are robust to alternative measures of firm size. Repeating the analysis using the natural log of both total sales and total assets led to similar results.


We measure leverage as the ratio of long-term debt to total capital. That is ) (Debt Equity Debt Leverage + = (2)

where Debt is measured as the sum of the firms traded (market value) and non-traded (book value) debt and Equity is the market value of equity. This yields results that are robust when compared to alternative measures of leverage.

Security specific variables include duration, credit ratings, and liquidity. We use duration to control for differences in maturity and coupon of the firm’s outstanding debt. Duration in this case is referred to as Macaulay duration, or the discounted time weighted cash flow of the security divided by its price. That is

= + × = K t t t Y P CF t DUR 1 (1 ) (3)

where CFt is the security cash flows at time t, t is the number of periods until the cash flow, Yis the

yield to maturity, and K is the number of cash flows. We compute the weighted average duration of the outstanding debt (Duration) as a linear combination of the weighted durations of each bond for each firm.

We control for differences in default risk using credit ratings (Ratings). Credit rating is computed as the average of both Moodys and S&P bond ratings and represents the average firm credit rating at the date of the yield observation (i.e., the credit ratings are not the historical rating at bond issuance but are updated as the bond seasons). Jewel and Livingston (1998) suggest that using the average of the Moody’s and S&P provides the most efficient measure of default risk premium.15 Bond ratings are computed using a conversion process in which AAA+ rated bonds are assigned a value of 23 and D rated bonds receive a value of 1. For example, a firm with an A1 rating from Moodys and an A+ from S&P would receive an average score of 18. Figure 1 provides the conversion numbers for both Moodys and S&P firm bond ratings used in the analysis.

A potential problem is that credit ratings may incorporate family ownership if it effects the costs of debt financing. Thus, we estimate the credit rating without the family ownership component. To achieve this, we regress family ownership on credit ratings. The error term from this regression incorporates the credit rating information without the influence or impact of family


ownership. We label the error term from this regression as (CREDIT) and use it as our primary measure of credit ratings in the multivariate analysis.

[Insert Figure 1 here]

We use the age of the bond as a measure of security liquidity. Researchers have found that liquidity is positively priced in the debt market (e.g., Beim (1992)). As more recently issued bonds are more liquid than older bonds, the age of an issue is commonly used as a proxy for bond liquidity (e.g., Elton and Green (1998)). The age of the bond (Age) is the length of time (in years) that a bond has been outstanding. This is a weighted average difference between the settlement date and the original bond issue date. For example, a bond with an observation date of April 30, 1993, and an issue date of January 31, 1990, would have an age of 3.25 years.

3.4. Descriptive and Univariate Statistics

Panel A of Table 1 presents the descriptive statistics for the variables used in the sample. Included are the mean, median, standard deviation, maximum and minimum values for family ownership, yield spread, duration, credit ratings, size, age, and leverage.

For the full sample, debt has an average yield spread of 136 basis points in excess of the Treasury yield, with a standard deviation of 110 basis points. Firm size, the natural log of total assets (in thousands), has a mean of $8.88, a standard deviation of $1.28, and a maximum and a minimum size of $12.78 and $4.40, respectively. The remaining variables in the sample are security specific. The mean traded debt has duration of approximately 6.3 years, a standard deviation of approximately 2.5 years, with a maximum duration of 13.6 years. Further, the mean-traded debt has been outstanding for 3.9 years, with a maximum age of 25.6 years. The median leverage ratio is 20% with a standard deviation of 13%. The family ownership measure (FAMFIRM) is a binary variable that takes a value of 1 for family firms and 0 otherwise.

Panel B of Table 1 describes the industry distribution of the sample using the standard Security Industry Classification (SIC) codes. Industries include: agriculture, forestry, and fishing, construction, manufacturing, transportation, wholesale and retail trade, and services (excluding financial and utility firms).


families on average hold 18% of the firm’s outstanding equity with a family member serving as CEO in 29.6% of the family firms. Outside CEOs or “hired-hands” make up the remaining 70.4% of CEOs in family firms. Panel C of Table 1 provides some initial univariate statistics between family and non-family firms. We present information on the cost of debt, firm size, and credit ratings for both family and non-family firms. Results of the univariate analysis imply that family firms use more leverage, are slightly smaller in size, but still enjoy a similar cost of debt capital and credit ratings. As size and leverage are both significant determinants of the cost of debt (e.g., Reeb et al. (2001)), this implies that family firms potentially enjoy a lower cost of debt financing. We explore this issue further in a multivariate framework.

[Insert Table 1 about here]

4. Multivariate Testing Results

4.1. Evidence on Yield Spreads with Family Ownership

In the primary specification, we test the cross-sectional relation between family ownership and the cost of debt financing, and various control measures. That is

Spreadi,t = A0 + A1 (FamFirmi,t ) + A2 (Duration i,t ) + A3 (Ratings i,t ) + A4 (Sizei,t ) +

A5 (Aget ) + A6 (Leverage i,t ) + A7 (Time_Dum,t ) + A8 (Ind_Dum it ) + ε (4)

where the dependent variable, Spread, is the bond yield in excess of the Treasury yield with corresponding maturity. The independent variables in our regression include family ownership (FamFirm), Duration, Ratings, Size, Bond Age, and Leverage, and both year and industry dummy variables. Our principal concern in the analysis is the family ownership coefficient estimate, A1. A negative coefficient would provide support for the hypothesis that family ownership reduces the agency costs of debt.

For our control variables, we anticipate that duration is negatively related to yield spread as higher duration securities demand higher coupons at issuance and greater chance of lower yields. However, as the yield spread is computed using the duration equivalent Treasury security, the construction of the dependent variable mitigates this concern. Ratings should be negatively related to yield spread as firms with lower credit ratings have a higher cost of debt financing. Size may also


be negatively related to yield spread as larger firms enjoy economies of scale and greater stability. However, size could be fully incorporated into credit ratings. Age of the firm’s outstanding bonds is included to control for differences in bond liquidity. We expect this variable to be positively related to yield spread as liquid securities (i.e., less seasoned) demand higher prices and lower yields. Leverage should also be positively related to the cost of debt financing, as higher debt usage is associated with higher cost of debt. That is, as the debt to equity ratio of a firm increases, the probability of default increases, which causes the rate of return to the bondholders to increase. Thus, we would expect a positive relation between leverage and yield spread. Finally, we include year and industry dummy variables to control for possible time and industry effects. Table 2 provides the predicted sign for each of the coefficient estimates.

[Insert Table 2 about here]

Column 2 of Table 2 presents the regression results using Equation (4). Our results indicate that family firms experience a lower cost of debt financing. The coefficient estimate on family firm is –33.504 with a t-statistic of –5.869, consistent with the notion that family and market forces provide strong incentives for founding families to monitor the firm and reduce agency conflicts.16

In terms of the control variables, the credit rating coefficient estimate is negative and significant at the 1% level, while the leverage coefficient estimate is not significantly different from zero.17 The coefficient on the size variable is significant and negative as anticipated and the bond age variable is positive and significantly different from zero at the 1% level. The duration coefficient estimate is insignificant, suggesting that the dependent variable controls for duration differences. Overall, our results indicate that family ownership is associated with a lower cost of debt financing18.

16 A concern with panel data is non-spherical disturbances. We control for serial correlation by subtracting the Treasury security yield from the firm yield and by including yearly dummy variables. We control for heteroskedasticity in the testing using heteroskedastic consistent t-statistics (e.g., White (1980)).

17 Excluding credit ratings and performing the regression, Equation (2), lead to a significant and positive effect of from leverage. This suggests that leverage effects on yield to maturity may be captured in the credit rating.

18 The relation between family ownership and the cost of debt financing may also be captured in credit ratings. Thus, we regress firm credit ratings on FamFirm along with various control variables. Similar to our reported results, the FamFirm coefficient estimate is positive and significant (at the 1% level). Thus, the credit rating results reinforce the evidence of a lower cost of debt financing for family firms.


4.2. Delineating between Family Founders, Descendents, and Outside CEOs

Morck, Shleifer, and Vishny (1988) suggest that firm founders and founder descendents, as CEO, have differing impacts on firm performance. In similar fashion, we explore the impact of the two potential CEO choices (Family Member or Outsider). To investigate the impact of CEO affiliation, we repeat the testing in equation (4) by adding dummy variables for each CEO type. Specifically, in columns 3 and 4 of Table 2, in the regressions, we include dummy variables (one per regression) for a family member as CEO (CEO_FAM), and for an outside hire as CEO (CEO_HIRE). Interestingly, we find that having a CEO as a family member is associated with a significantly higher cost of debt financing (15.80 basis points, p-value <5%), while outside CEOs or “hired-hands” appear to have no significant effect on bond yields.

In further testing, we delineate between the founder as CEO (CEO_FOUNDER) and founder descendants as CEO (CEO_DESC). Our results are shown in columns 5 and 6 of table 2 and indicate founder descendants acting as CEO increase debt costs while founders bear no significant relation to the cost of debt. Seemingly, bondholders view passing firm leadership from founders to their heirs as detrimental to their wealth and thus require higher yields. The F-tests however, indicate that after even after controlling for CEO type, family firms still have a lower overall cost of debt. Family firms with “hired-hands”, founders, and founder descendants enjoy a 36.7, 32.3, and 17.9 basis point advantage over non-family firms (each significant the 1% level), respectively.

4.3. The Impact of Independent Monitors

In Table 2, we also explore two independent firm monitors that potentially affect the firm’s cost of debt to assess the robustness of our results. Other large shareholders or blockholders, in seeking to maximize firm value, also have incentives to protect bondholder interests to achieve lower long-term financing costs for the firm. We define blockholders as entities holding 5% or more of the firm’s share and having no other relationship to the firm except their ownership (e.g., pension funds, mutual funds, etc.). The coefficient estimate on outside blockholders is positive but insignificant in Column 7 of Table 2 suggesting these entities have no effect on the cost of debt financing. From an empirical perspective, our results suggest that founding families have substantially different incentive structures than institutional investors.


protect bondholder wealth to reduce the cost of future debt financing. Following the governance literature, we classify board members as inside, affiliated, and independent directors using the classification scheme of Brickley, Coles, and Terry (1994). Directors currently employed by the firm or retired and their immediate families are insiders. Affiliated or gray directors are those board members with existing or potential business ties to the firm. Outside directors are members whose only affiliation with the firm is their directorship. We find that adding this variable to the analysis increases the explanatory power of the testing. The coefficient estimate for outside directors, in Column 8 of Table 2, is –38.369 basis points suggesting that as board independence increases by 10%, the cost of debt decreases by 3.8 basis points. This evidence is consistent with the notion that outside directors have a direct bearing on firm performance by lowering the cost of debt.19

Consistent with the results in the prior tests, the family ownership coefficient estimate is also negative and significant (1% level) after controlling for other potential monitors. These results are also economically significant indicating that after controlling for firm and debt specific attributes, family firms have about 39.97 basis point lower cost of debt than in non-family firms. Thus, the average family firm in our sample enjoys more than a one third percentage point lower cost of debt financing relative to their non-family firm counterparts. This is similar in magnitude to the spread between AA and A rated debt (based on the LBBD database) and as such represents an important competitive advantage for family firms.

4.4. On the Linearity of Family Ownership and the Cost of Debt

Prior research on ownership structure suggests that the impact of ownership structure on firm performance is non-linear (e.g., Bagnani et al. (1996), McConnell and Servaes (1990), Morck, Shleifer and Vishny (1988)). Consistent with prior literature, we explore piece-wise linear regression models with one and two breakpoints. Using switching point regression techniques that estimate breakpoints based on minimizing the unexplained variance of the regression model, we find that a 2-piece model with a breakpoint at 12% best explains the ownership/debt relation.20 Based on a 12% ownership breakpoint, we develop an additional variable to describe family holdings. That is

19 Separate subset testing for both family and non-family firms indicates that both groups exhibit a lower cost of debt financing with outside directors.

20 We find this method preferable to arbitrarily establishing breakpoints. We also employed three-piece models as well and found similar results. As such we report our testing based on the two-piece models.


Fam Over 12 =1 if founding families holdings are greater than 12% of the firm’s shares and 0 otherwise.

Our expectation is that families with the greatest level of equity ownership will have the greatest impact on the cost of debt financing. As such, we expect both FamFirm and and Fam Over 12 to be negatively related to the cost of debt financing. The test specification is21

Spreadi,t = B0 + B1 (FamFirmi,t ) + B2 (Fam Over 12i,t ) + B3 (Duration i,t ) +

B4 (Ratings i,t ) + B5 (Sizei,t ) + B6 (Age i,t ) + B7 (Leverage i,t )

+ B8 (Time_Dum,t ) + B9 (Ind_Dum it ) + ε (5)

We report the results of our regressions in Table 3. The coefficient estimate for FamFirm is consistent with our prior results and indicates that founding families have a lower cost of debt financing. Family firms with one to twelve percent ownership stakes enjoy about a 49.54 basis point lower cost of debt financing than non-family firms. However, beyond a 12% ownership stake, we note an incremental increase in debt costs of 21.89 basis points suggesting that large family holdings potentially lead to wealth expropriation form bondholders or families entrench themselves at the expense of other claimants. However, after controlling for high ownership stakes, we find that family firms still enjoy a 27.64 basis point lower cost of debt than non-family firms.

[Insert Table 3 about here]

4.5. Excess Bondholder Value and Family Ownership

The standard performance measure in the ownership literature is primarily based on the excess market value of the firms' equity (Tobin’s Q). One common method used to measure excess value computes the difference between (or ratio of) the market value of equity and its book value (or replacement value). This type of excess value measure, however, may be problematic when used to compute excess bondholder value because bonds have varying coupon rates and face values.22

21An alternvative approach is to replace FamFirm with an indicator variable for firms with less than 12% ownership.

We find similar results using either approach.

22 These biases are referred to in the fixed income literature as coupon bias and weighting bias (e.g., Mansi and Reeb (2001)). Coupon bias refers to the difference between the term-structure yield and the par yield (i.e., coupon rate) for any


To remedy this problem, the valuation of the firm’s debt must follow a two step procedure. First, we compute the value of the debt based on effective maturity (or duration) rather than remaining term to maturity. This remedies the effect of different coupons since effective maturity transforms the security to its equivalent zero-coupon security. Second, the total value of the firm’s debt must be computed as a linear summation of the weighted values of each debt instrument, with the weights being the fraction of each bond relative to the total traded debt outstanding. Following this procedure, we measure excess bondholder value (EBV) as the difference between the market value of a corporate debt security and a Treasury security with a corresponding duration. In other words, we are in interested in computing the value attributed to the return in excess of the risk-free rate, or the excess value due to firm specific attributes. That is



EBV = − (6)

Where MKTDEBT is the imputed market value of the firm's traded debt per $1,000 face value after converting the debt to its equivalent zero-coupon and TSYDEBT is the duration equivalent Treasury security price. As the prices are both in terms of a $1,000 bond of equivalent maturity, the result is an excess value metric expressed per $1,000 bond.

Panel A of Table 4 provides the mean, median, and standard deviation for excess bondholder value for the firms in our sample. We find that the average firm in our sample has about a $48 discount relative to its equivalent Treasury security price. Since excess bondholder value is computed by subtracting the duration equivalent Treasury security, this measure is negative by construction.23 Similar to the equity-based evidence, the higher the EBV metric, the higher the price of the firm’s outstanding debt.

To investigate the impact of family ownership on excess bondholder value, we use the specification in Equation (4), with EBV as the dependent variable. The principal variable of interest in this analysis is the A1 coefficient estimates.

[Insert Table 4 Here]

given term to maturity. This bias has a direct effect on duration (or effective maturity) since bonds with larger coupon rates have lower duration than bonds with lower coupon rates. Weighting bias occurs when we use the book value of the debt rather than the market value of the debt to compute the weights of each debt instrument.

23 In essence, this measure of excess bondholder value represents that portion of the price due to firm specific attributes and abstracts away from economy wide changes in the price of debt capital.


Panel B in Table 5 provides the regression results using the modified Equation (4). The results indicate a positive and significant (at the 1% level) relation between bondholder excess value and family firms. Specifically, the results indicate that excess bondholder value for family firm is, on average, about $8.79 greater than in non-family firms. As the average discount is about $48, this indicates that bondholders of family firms have about an 18% premium. The control variables provide similar results to the prior testing and have the correct signs.

5. Robustness Testing

An assumption of our analysis is that the specification and proxies adequately measure the appropriate attributes. We find that our results are also robust to various alternative specifications. In the first alternative specification, we add a measure of firm risk. Because of the undiversified nature of founding-family portfolios, these firms may choose projects that limit or mitigate the amount of risk that firms undertake. While this should lower the agency cost of debt, other aspects of family ownership (i.e., monitoring) may also play a role in reducing the agency costs of debt. To disentangle these effects, we control for this eventuality by including a measure of project risk that we define as the standard deviation of monthly stock returns for the previous 60-months. Using this model, we find that family firms still enjoy a 37 basis point advantage over non-family firms. We also added intangible assets (Intangibles) as another control variable to Equation (5). Intangibles potentially reflect a lower ability of a firm to pay creditors in case of liquidation. The results of this confirm our initial findings that family ownership is associated with a lower cost of debt.

As in any corporate finance research there is a potential endogeneity problem. Specifically, the concern is whether lower firm risk leads to greater family ownership (and vice versa). While, we explicitly control for firm risk above, an alternative approach is to use a 2 stage least squares framework. Following, Himmelberg, et al. (1999) in developing an instrumental variable for ownership, we find similar results to those reported in Tables 2 - 4. Specifically, using the instrumental variable approach, we find that family firms are associated with about a 35 basis point reduction in the cost of debt financing.

Third, to test the sensitivity of our results in the presence of outliers and influential observations, we eliminate observations denoted as outliers and/or influential observations using the


R-Student statistic and the DFFITS statistic.24 These tests examine a sample to determine if any observations have a dramatic effect on the fitted least-squares function. The results were similar to those reported in Table 3 and do not change substantively when truncated for outliers at the largest one percent, three percent, and five percent levels at each tail of the distribution for each variable in the model. Further, as firm year observations may intensify the outlier bias, we repeated the analysis using pooled regressions, which also led to similar results.25

We also allow for a nonlinear relation between bond yield spreads and credit ratings. As many institutions are barred from holding securities below a certain class, this may create nonlinearities. Likewise, the initial level of the credit ratings is also important and should be tested (e.g., a jump from AAA to AA+ may be different than the jump from BBB+ to BBB). Therefore, we use both a binary variable approach (with investment grade coded as 1) and a 23 piece-wise linear regression with 22 dummy variables to denote each credit ratings.26 The results of these regressions are consistent with the primary specification results regarding the impact of founding family ownership, and indicate that the linear credit specification is the most robust.

In further tests, we consider an alternative method of measuring bond liquidity. Our primary specification utilized age as a proxy for liquidity. However, a nonlinear specification may be more appropriate, because bond liquidity appears to decay exponentially with age (e.g., Beim (1992)). Therefore, we replace age with the natural log of age. Liquidity can also be measured using a binary variable to denote bonds less than three years old. Regressions using these two alternate measures are consistent with our primary regression, suggesting that family ownership is indeed associated with lower cost of debt. The number of bond issues a firm has outstanding can also be used as a measure of liquidity. Repeating the analysis including the number of outstanding issues also leads to similar results.

As the bankruptcy literature suggests that firm liquidity and volatility are important variables in measuring default risk, we repeat our analysis using the coverage ratio as a proxy for firm liquidity, and stock price variability to measure volatility. Both the coverage ratio coefficient estimate and the

24 Observations with an R-Student greater than 3 or a DFFITS greater than 1 are considered outliers or influential observations, respectively. Neter, et al (1996) provides a thorough treatment of outliers and influential observations. Surprisingly, we do not detect serial correlation in the sample. However, we do detect heteroskedasticity and therefore the results are reported using heteroskedastic consistent t-statistics.

25 Our primary testing is based on observation per firm year (i.e., panel data). For robustness we consider collapsing the data to one observation per firm (i.e., a pooled regression). In the pooled regression the data for each firm is averaged across the sample and the regression is based on this pooled set.

26 We also tried a non-linear specification using the square of the firm’s credit rating. This approach also led to similar results.


volatility coefficient estimate are insignificant, and the results are consistent with those reported. We also consider allowing for a non-linear relation between the yield spread and firm leverage. Specifically, we incorporate the square of leverage as another potential control variable and find that our results of a negative relation between the cost of debt and family ownership remains unchanged.

Realizing that the relation between family ownership and yield spread may not be stable over time, especially during the 1994 period when the Fed raised interest rates seven times in succession, we use a dummy variable to denote the pre-1995 period along with period subset regressions. The results corroborate with those reported. In addition, we perform the analysis using the several different fractional rules of family ownership. The results gave similar inferences regarding our research question. We also control for debt structure by including the proportion of senior debt to total debt in our analysis. Once again we find a negative relation between family ownership and the cost of debt financing. Overall, the results suggest a significant relation between family equity ownership and the agency cost of debt.

6. Conclusion

Diversified shareholders have incentives to expropriate bondholder wealth by investing in risky high-expected return projects since they capture the excess returns if this strategy is successful, while debtholders bear the costs of failure. Recognizing these potential conflicts of interest, bondholders require higher interest rates. In this context, prior research focuses on the use of bond covenants and callable debt to minimize these agency costs of debt. In contrast, our research explores the relation between founding family ownership/influence and the agency cost of debt. Thus, we investigate the impact of concentrated versus dispersed equity ownership on the agency cost of debt. To the best of our knowledge, this is the first empirical study to analyze directly how ownership structure affects the cost of debt financing.

Using a sample of firms from the Lehman Brothers Bond Database and the S&P 500, we document that founding-family ownership is common with families present in about 30% of firms and holding 18% of the outstanding equity. Because these shareholders typically have undiversified portfolios, are concerned with firm and family reputation, and often desire to pass the firm onto their descendants, we contend they represent a unique class of shareholders that potentially affect agency costs. Our analysis indicates that founding-family ownership reduces the cost of debt financing. Specifically, we find that family firms enjoy a 39.97 basis point lower cost of debt


financing. The greatest value gains from family ownership occur when families hold 1 to 12% of the firm’s shares. Above a 12% stake, debt costs increase but are still lower than those found in non-family firms.

Families, beyond their ownership stake, can also exert additional control and possibly reduce agency problems by placing one of their members in the CEO position. Contrary to this notion, we find that CEOs who are descendants of the founder appear to raise debt costs. Regardless of CEO status though, family firms enjoy a lower cost of debt financing. We also find that governance systems traditionally related to equity ownership appear to affect debt costs. Specifically, we find that bond yields diminish as board independence increases, while outside blockholders do not appear to influence yields.

Overall, we find strong evidence that equity-ownership structure significantly influences the conflicts of interests between shareholders and bondholders. Because of the unique incentives generated by long-term commitments to the firm, undiversified portfolios, and familial pressure, founding families appear to reduce agency conflicts between the firm’s equity and debt claimants and thereby reduce the cost of debt financing. Our analysis suggests that bondholders view founding-family ownership as an organizational structure that better protects their interests.



Amihud, Y. and B. Lev, 1981, Risk reduction as a managerial motive for conglomerate mergers. The Rand Journal of Economics, 12, 605-618.

Anderson, R. and J. Bizjak, 2001, Who’s minding the store?: Founding families and minority shareholders. Working Paper, American University and Portland State University.

Bagnani, E., N. Milonas, A. Saunders, and N. Travlos, Managers, owners and the pricing of risky debt: An empirical analysis. Journal of Finance 49, 453-478.

Beim, D., 1992, Estimating bond liquidity. Working Paper, Columbia University.

Berle, A. and G. Means, 1932, The Modern Corporation and Private Property. New York, Mac Millon.

Byrd, J. and K. Hickman, 1992, Do outside directors monitor managers? Evidence from tender offer bids. Journal of Financial Economics 32, 195-222.

Cantor, R., F. Packer and K. Cole, 1997, Split ratings and the pricing of credit risk. Journal of Fixed Income 7, 72-82.

Chami, R., 1999, What’s different about family business?. Working Paper, University of Notre Dame and the International Monetary Fund.

Demsetz, H., and K. Lehn, 1985, The structure of corporate ownership: Causes and Consequences. Journal of Political Economy 93, 1155-1177.

Duffie, G. The Relationship between Treasury Yields and Corporate Bond Yield Spreads. Journal of Finance, 103 (1998), 2225-2241.

Elton, E. and C. Green, 1998, Tax and liquidity effects in pricing government bonds. Journal of Finance 53, 1533-62.

Elton, E. and M. Gruber, 1995, Modern Portfolio Theory and Investment Analysis, New York, John Wiley & Sons.

Errunza V., and L. Senbet, 1981, The effects of international operations on market value of the firm: theory and evidence. Journal of Finance 36, 401-417.

Errunza V., and L. Senbet, 1984, International corporate diversification, market valuation and size-adjusted evidence. Journal of Finance 34, 727-745.

Fama, E., 1980, Agency problems and the theory of the firm. Journal of Political Economy 88, 288-302.

Gibbons, R., and K. Murphy, 1992, Optimal incentive contracts in the presence of career concerns: Theory and evidence. Journal of Political Economy 100, 468-501.

Goldfield, S. M. and R. E. Quandt, 1973, The estimation of structural shifts by switching regressions. Annals of Economics and Social Measurement 2, 475-485.


Himmelberg, C., R. Hubbard, and D. Palia, 1999, Understanding the determinants of managerial ownership, Journal of Financial Economics, 53: 353-384.

Holmstrom, B., and R. Costa, 1986, Managerial incentives and capital management. Quarterly Journal of economics 101, 835-861.

Jensen M. and W. McKling, 1976, Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics 3, 305-360.

Jewel, J. and M. Livingston, 1998, Split ratings, bond yields, and underwriter spreads. Journal of Financial Research 21, 185-204.

Kalay, A., 1982, Stockholder-bondholder conflict and dividend constraints. Journal of Financial Economics 10, 211-233.

Mansi, S. and D. Reeb, 2001, Determinants of the maturity structure of public corporate debt. Working Paper, Texas Tech University and American University.

Morck, R., A. Shleifer, and R. Vishney, 1988, Management ownership and market valuation: An empirical analysis. Journal of Financial Economics 20, 293-315.

Myers, S., 1977, Determinants of corporate borrowing. Journal of Financial Economics 5, 146-75. Mueller, H. and R. Inderst, 2001, Ownership concentration, monitoring, and the agency cost of

debt, Working Paper, University of Mannheim.

Nelson C. and A. Siegel, 1987, Parsimonious Modeling of Yield Curves. Journal of Business 6, 473-489.

Neter, J., M. Kutner, C. Nachtsheim, and W. Wasserman, 1996, Applied Linear Regression Models. Irwin-McGraw Hill Publishing.

Reeb, D., S. Mansi, and J. Allee, 2001, Firm internationalization and the cost of debt financing: Evidence from non-provisional publicly traded debt. Journal of Financial and Quantitative Analysis, Forthcoming.

Sarig, Oded and Arthur Warga, 1989, Some empirical estimates of the risk structure of interest. Journal of Finance 44, 1351-1361.

Tufano, P., 1996, Who managers risk? An empirical examination of risk management practices in the gold mining industry. Journal of Finance 51, 1097-1137.

Weisbach, M., 1988, Outside directors and CEO turnover. Journal of Financial Economics 20, 431-461.

White, H., 1980, A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48, 817-838.

Woidtke, T., 2001, Agents watching agents?: Evidence from pension fund ownership and firm value. Journal of Financial Economics, Forthcoming.


Table 1.

Sample Description

Panel A: Descriptive Statistics for Variable Measures

This table provides summary statistics for the data employed in our analysis. The data set is comprised of 1,052 firm year observations from 1993-1998. The descriptive statistics variables include: the fractional ownership of the family, weighted average yield spread (Spread), weighted duration of debt (Duration), average credit rating (Ratings), firm size (Size), average bond age (Age), and firm leverage (Leverage).

Variables Mean Median DeviationStandard Maximum Minimum

Spread (basis points) 135.961 102.7006 109.454 1067.866 2.239

Duration (years) 6.287 6.276 2.454 13.621 0.0830 Credit Ratings 15.979 16.0000 3.209 22.143 1.0000 Size 8.877 8.705 1.28 12.782 4.398 Age (years) 3.917 3.511 2.689 25.655 0.033 Leverage 21.972 20.342 13.331 94.304 0.000 Family Ownership 0.300 0.000 0.459 1.000 0.0000

Panel B: Industry Data

This panel includes the number of firm-year observation for each industry group in the sample using single digit SIC codes.


Code Titles of Industries Firm-Year Obs.Number of

1 Mining 41 2 Construction 359 3 Manufacturing 322 4 Transportation 62 5 Wholesale Trade 138 6 Retail Trade 82 7 Agricultural Services 42 8 Forestry 6

Panel 1C: Univariate Analysis

This table provides data on the average cost of debt, size, and credit ratings for both family and non-family firms.

Firm Type Market Cost of Debt(Spread) Size Credit Rating

Family Firms 136.053 8.495 16.147


Table 2.

Yield Spread and Family Ownership

This table gives the estimated coefficients from regressing corporate yield spreads (the difference between the weighted average yield on the firm’s outstanding debt and the yield on a Treasury security with a similar maturity) on a binary indicator of family ownership and various control variables. The specification used is

Spreadi,t = A0 + A1 (FamFirmi,t ) + A2 (Duration i,t ) + A3 (Ratings i,t ) + A4 (Sizei,t ) +

A5 (Aget ) + A6 (Leverage i,t ) + A7 (Time_Dum,t ) + A8 (Ind_Dum it ) + ε

where the independent variables are: a 0 or 1 indicator of family firms (FamFirm), weighted average duration (Duration), yield spread (Spread), average credit rating (Ratings), firm size (Size), average bond age (Age), firm leverage (Leverage),and dummy variables for both time period and industry.

Variable Sign SpecificationPrimary FamilyCEO HIRECEO FOUNDERCEO DescendantCEO BlockholdersOutside DirectorsOutside

Column (1) (2) (3) (4) (5) (6) (7) (8) Intercept 513.320* (13.984) 513.351*(13.927) 512.768*(13.943) 513.175*(13.965) 514.189*(13.936) 502.461*(12.473) 524.201*(13.598) FamFirm - -33.504* (-5.869) -37.344*(-6.871) -26.563*(-3.219) -33.584*(-5.887) -36.962*(-6.672) -32.601*(-5.782) -39.965*(-5.907) Duration - 1.533 (1.629) (1.471)1.396 (1.579)1.493 (1.628)1.532 (1.462)1.391 (1.634)1.540 (1.576) 1.490 Ratings - -21.892* (-15.089) (-15.055)-21.945* (-15.092)-21.802* (-15.006)-21.887* (-14.973)-22.038* (-14.992)-21.669* (-15.081)-21.747* Size - -47.231* (-12.622) (-12.427)-46.897* (-12.522)-47.030* (-12.598)-47.225* (-12.455)-46.914* (-12.129)-46.535* (-12.798)-46.785* Age + 7.033* (5.458) (5.423)7.057* (5.442)7.071* (5.441)7.041* (5.371)6.957* (5.367)6.990* (5.434)7.058* Leverage + .105 (.385) (.139).039 (.324).089 (.387).105 (.057).016 (.421).115 (.431).117 CEO ? 15.799** (1.975) (-1.326)-10.143 (0.121)1.293 19.0816**(1.980) Outside Blockholders 21.847 (0.675) Outside Directors -38.369** (-2.422) Adjusted R Square 0.558 0.559 0.558 .557 0.559 .557 .560


Table 3.

Family Ownership and Control

This table gives the estimated coefficients from regressing corporate yield spreads (the difference between the weighted average yield on the firm’s outstanding debt and the yield on a Treasury security with a similar maturity) on a binary indicator of family ownership and various potential control variables. We also add a second indicator variable of high family ownership (above 12%).

Variable Family OwnershipHigh

Intercept 520.618* (13.436) FamFirm -49.536* (-7.527) Duration 1.690*** (1.778) Ratings -21.680* (-14.972) Size -46.767* (-12.748) Age 7.197* (5.450) Leverage .147 (.534) Outside Directors -35.025* (-2.213) Fam Over 12% 21.892* (2.887) Adj. R-Square .563

*, ** Significant at the 1% and 5% level, respectively. The t-values, given in parenthesis below each estimate, are corrected for heteroskedasticity.


Table 4.

Excess Bondholder Value and Family Ownership

This table provides sample statistics results for excess bondholder value. Excess bondholder value is defined as the difference between the market value of a corporate debt security and a Treasury security with a corresponding duration.

Panel A: Simple Statistics

Variable Mean Median DeviationStandard

Excess Bondholder Value -48.856 -42.281 33.264

Panel B: Multivariate Analysis

Variable Excess Bondholder Value DirectorsOutside

Column Number (1) (2) Intercept -138.203* (-11.662) -141.094*(-11.478) FamFirm 8.787* (5.419) 10.418*(5.808) Duration -4.849* (-17.543) (-17.462)-4.838* Ratings 6.287* (14.508) (14.502)6.248* Size 13.421* (11.677) (11.810)13.303* Age -1.741* (-4.131) (-4.099)-1.747* Leverage -0.135 (-1.534) (-1.571)-0.138 Outside Directors 10.110** (2.056) Adj. R-Square .582 .584

*, ** Significant at the 1% and 5% level, respectively. The t-values, given in parenthesis below each estimate, are corrected for heteroskedasticity.


Figure 1.

Bond Rating Numerical Conversions

This figure provides bond rating conversion codes for Moody’s and S&P ratings used in the analysis.


Number Moody’sRatings RatingsS&P

23 Aaa+ AAA+ 22 Aaa AAA 21 Aa1 AA+ 20 Aa2 AA 19 Aa3 AA-18 A1 A+ 17 A2 A 16 A3 A-15 Baa1 BBB+ 14 Baa2 BBB 13 Baa3 BBB-12 Ba1 BB+ 11 Ba2 BB 10 Ba3 BB-9 B1 B+ 8 B2 B 7 B3 B-6 Caa1 CCC+ 5 Caa2 CCC 4 Caa3 CCC-3 Ca CC 2 C C 1 D D


Related documents

ACE 3β+2α+2δ High Spectral Resolution Lidar (HSRL) Instrument Concept  Measurements – Backscatter at 355, 532, 1064 nm (3β) – Extinction 355 and 532 nm (2α) – Depolarization

In this paper, a crypto-biometric scheme, based on fuzzy extractors, by using iris templates, is proposed, i.e., we propose a new system in order to permit a user to retrieve a

Table 1: Resource and user attributes favourable for self-governance: Comparing natural CPRs and the collective reputation of local producers.. Natural CPRs (Ostrom 2005, 244–5)

The outputs of this study, ADM system development process and the sources and remedies of bias for each step of the process, can be used by businesses to eliminate algorithmic

This paper is a space syntax, empirical evidence-based examination of supportive housing facilities for homeless individuals in North America. It contributes a

A number of folks think about if dates are actually consumed alongside fruits are more nourishing than dates consumed alone.. The solution is actually a big certainly, however the

To quantify these deviations from theory, we tallied the number of respondents who displayed any of the following patterns: (1) when asked about foreign businesses