DEBT MATURITY STRUCTURE, AGENCY COSTS, AND FIRM VALUE: EVIDENCE FROM 1973­2004 Pornsit Jiraporn * , Assistant Professor Pennsylvania State University – Great Valley Shenghui Tong, Associate Dean Chinese Academy of Finance and Economics, Beijing ABSTRACT Based on agency theory, this study seeks to ascertain the impact of debt maturity structure on firm value. Short maturity debt has been argued to mitigate agency costs by reducing underinvestment problems. Further, short­term debt can alleviate the agency costs of managerial discretion by exposing management to more frequent monitoring by external parties. Due to its role in curbing agency costs, we hypothesize that the use of more short­term debt enhances firm value. Employing a substantial data set with over 100, 000 observations across 32 years, we find empirical evidence consistent with this hypothesis. Moreover, the evidence reveals that the positive association between short­term debt usage and firm value is more pronounced in firms with higher agency costs. We argue that the beneficial effect of short­term debt is less necessary in firms with low agency costs. As a result, the use of short­term debt does not increase value in these firms. Finally, cognizant of potential endogeneity, we examine the impact of changes in debt maturity structure on changes in firm value. The evidence indicates that a reduction in the proportion of long­term debt is associated with an increase in firm value. JEL Classification: G30, G32, G34 Keywords: Debt maturity, firm value, agency theory, agency costs, short­term debt INTRODUCTION The literature on capital structure has primarily focused on the optimal mix between debt and equity. More recently, however, a great deal of attention has been given to another aspect of capital structure, i.e. debt maturity structure. The overwhelming majority of the literature in this area is devoted to the determinants of debt maturity. Surprisingly, very little effort has been made to ascertain the actual impact of debt maturity on firm value. This study fills the void in the literature by investigating the impact of debt maturity structure on firm value. Further, we employ agency theory to explain a manner in which debt maturity influences firm value. A critical advantage of this study lies in the comprehensive sample size, which encompasses over 100,000 observations across more than 14,000 firms over 32 years, the largest in the literature so far. Previous literature suggests that debt maturity structure may affect firm value. Shorter maturity debt may enhance firm value in different ways. First, Myers (1977) argues that shorter maturity debt is beneficial because it alleviates the underinvestment and asset substitution problems. Second, Rajan and Winton (1995) show that short­term debt permits lenders the flexibility to effectively monitor managers with minimum effort. Furthermore, short­term debt forces firms to visit the capital markets more frequently, exposing managers to careful scrutiny by external parties, thereby mitigating agency costs. Likewise, Stulz (2000) asserts that “short­term debt can be an extremely powerful tool to monitor management”. For these reasons, firms using a higher proportion of short­term debt should experience * Contact author email: [email protected]
higher firm value, ceteris paribus. On the contrary, it could be argued that longer maturity debt is helpful and should improve firm value. For instance, long­term fixed­rate debt protects the borrower against fluctuation in interest rates. Moreover, the transaction costs of rolling over short­term debt may make long­term debt preferable. Because there are arguments both in favor of and against the use of short­term debt, the association between the proportion of short­term debt usage and firm value is an empirical question. We attempt to shed light on this question by investigating how debt maturity structure influences firm value, as measured by Tobin’s q. The evidence demonstrates a positive association between the proportion of short­term debt usage and firm value, suggesting that short­term debt is beneficial. We further attempt to identify a manner in which short­term debt improves firm value. We focus on the role of short­term debt in reducing agency costs of equity. Agency theory would suggest that firms where agency costs are more severe should find short­term debt more beneficial (to the extent that agency costs are mitigated by short­ term debt). Using free cash flows to proxy for the extent of potential agency conflicts, we hypothesize that the positive association between short maturity debt and firm value should be more pronounced in firms with higher free cash flows. The empirical evidence lends support to this hypothesis. In addition, we hypothesize that regulation may help alleviate agency costs and make superfluous the role of debt maturity in reducing agency problems. The evidence does not lend credence to this notion, however, as we find that, even in regulated firms, more short­term debt usage is associated with higher firm value. Moreover, we surmise that the Sarbanes­Oxley Act (SOX) may alter the association between debt maturity and firm value as SOX demands stricter corporate governance that may substitute for debt maturity in controlling agency costs. The results confirm this hypothesis as we find that the beneficial effect of short­term debt on firm value vanishes after the passage of SOX in 2002. Mindful of endogeneity, we check the robustness of our results by examining the impact of changes in debt maturity on changes in firm value. This approach minimizes the potential endogeneity problem. 1 The results reveal that firms that adopt a higher proportion of short­term debt experience an increase in firm value, consistent with the prediction of agency theory and the free cash flow hypothesis. The results of this study make a number of contributions to the literature. Most importantly, we add to the literature in capital structure by showing that debt maturity structure does matter to firm value. Second, the literature in agency theory also benefits as the evidence implies that agency costs can be mitigated by the use of short­term debt. Third, we employ the most comprehensive sample in the literature, encompassing over 100,000 observations across over three decades. Such a large sample makes it likely that our results can be generalized. The structure of the rest of this article is as follows. Section II delineates the motivation and the hypothesis development. Section III discusses the sample formation and the data description. Section IV displays and discusses the empirical evidence. Finally, Section V offers the concluding remarks. MOTIVATION AND HYPOTHESIS DEVELOPMENT a. Motivation The structure of debt maturity is irrelevant for firm value under perfect market assumptions (Stiglitz, 1974). The subsequent theories concentrate on introducing market imperfections such as information asymmetry (Flannery, 1986; Diamond, 1991; Kale and Noe, 1990; Goswami, Noe, and Rebello, 1995), taxation (Brick and Ravid, 1985; Lewis, 1990; Brick and Ravid, 1991; Ravid, 1996), agency costs of debt (Myers, 1977), and agency costs of equity (Datta, Iskandar­Datta, and Raman, 2005; Rajan and Winton, 1995; Jiraporn and Kitsabunnarat, 2007). Motivated by agency theory, we explore the 1 An alternative approach would be simultaneous equations. However, given the nature of our study, it is difficult to estimate simultaneous equations for several reasons. First, it is nearly impossible to find instrumental variables that are truly exogenous. Second, even if such variables could be identified, they would be unlikely to be available for the entire sample period of 32 years. Third, it has been acknowledged in the literature that simultaneous equations are very sensitive to the choice of instrumental variables and can produce vastly different results. For the above reason, we elect to employ an alternative approach that should be equally effective in coping with endogeneity and is quite well­known in the literature, i.e. examining the impact of changes in debt maturity on changes in firm value (Carter, Rogers, and Simkins, 2006).
role of debt maturity in controlling agency costs of equity and investigate how debt maturity structure affects firm value. The vast majority of the literature in this area seeks to ascertain the determinants of debt maturity. Although useful, most prior studies fail to answer the most critical question, i.e. how debt maturity structure impacts firm value? This study is designed to empirically answer the question. In addition, we explore one mechanism through which debt maturity influences firm value. Specifically, we concentrate on the role of debt maturity in mitigating the agency costs of equity. b. Hypothesis Development Agency theory posits that short maturity debt can be valuable. First, short­term debt helps mitigate the agency costs of debt by resolving the underinvestment and asset substitution problems (Myers, 1977). Second, short maturity debt has the additional benefit of alleviating the agency costs of managerial discretion by subjecting managers to more frequent monitoring by underwriters, investors, and rating agencies at issuance (Datta et al.., 2005). As short­term debt comes up for frequent renewal, Stulz (2000) argues that short­term debt can be an extremely powerful mechanism for managerial oversight. Furthermore, Rajan and Winton (1995) offer a theoretical model that suggests that short­term debt provides lenders with the flexibility to efficaciously monitor management with minimum effort. In addition, Datta et al. (2005) report a significant inverse relationship between corporate debt maturity and managerial ownership. Because agency costs of equity originate from the divergence of ownership and control, they argue that this is evidence that debt maturity structure is related to agency conflicts. Finally, Jiraporn and Kitsabunnarat (2007), examining the impact of shareholder rights on debt maturity structure, finds an inverse relationship between the strength of shareholder rights and debt maturity. Jiraporn and Kitsabunnarat (2007) contend that managers of firms with weak shareholder rights eschew choosing short­term debt to minimize frequent external monitoring, again, suggesting the presence of agency conflicts. The evidence in Jiraporn and Kitsabunnarat is also strongly supported by Harford, Li, and Zhao (2007) and Benmelech (2006). Given the theoretical arguments and prior empirical evidence, we surmise that there should be an inverse association between corporate debt maturity and firm value. In other words, given the benefit of short­term debt, firms that carry a larger proportion of short­term debt should be more valuable. Additionally, we investigate the role of short­term debt in mitigating the agency costs of managerial discretion. The ability of short­term debt to combat agency conflicts should be more valuable in firms with more severe agency conflicts. Hence, we hypothesize that the positive relationship between short­ term debt and firm value should be more pronounced in firms with higher agency costs. 2 SAMPLE FORMATION AND DATA DESCRIPTION a. Sample Selection COMPUSTAT reports the amount of long­term debt at fiscal year end which is payable in more than 1 year through more than 5 years. To gauge the maturity structure of a firm’s debt, we discard any firm­year observation where the total debt maturity is less than 0% or more than 100%. We include a number of firm characteristics as control variables. Firms with missing data are excluded. COMPUSTAT includes data on debt maturity as far back as 1973. Thus, our sample spans 32 years from 1973 to 2004. 3 The final sample encompasses 104,124 firm­year observations across 14,920 firms. Our sample seems to be the largest and most comprehensive in the literature. Table 1 shows the sample distribution by year. 2 An alternative hypothesis is that if firms make optimal choices (given their constraints), then, in equilibrium, there is expected to be no association between debt maturity and firm value. As each firm chooses its value­maximizing debt maturity, any differences in firm value would not result from differences in debt maturity across firms. We argue, however, that agency conflicts make a firm’s debt maturity structure deviate from the optimal level. Thus, debt maturity structure may affect firm value. 3 Due to the long period of our sample, the data are adjusted for inflation by the Consumer Price Index (CPI).
b. Debt Maturity Structure Panel A of Table 2 documents summary statistics on debt maturity structure. The table reports the distribution of the percentage of total debt maturing in more than 1 year through more than 5 years. 4 We document that, on average, 86.91% of total debt matures in more than 1 year, 75.14 matures in 2 or more years, 66.00% matures in 3 or more years, 58.84% in 4 or more years and, finally, 52.49% in 5 or more years. c. Firm Characteristics Panel B of Table 2 reports the salient firm characteristics. Firm size averages 1,129 million (97.73 median). Total assets average 1,180 million (83.11 median). The average Tobin’s q, as computed by Chung and Pruitt (1994), is 2.28 (0.90 median). The market­to­book ratio of equity averages 1.25 (0.43 median). The ratio of EBITDA over total assets averages ­5.79% (11.60% median). Finally, the total debt ratio averages 36.50% (27.60% median). EMPIRICAL RESULTS a. Univariate Analysis We attempt to ascertain the impact of debt maturity on firm value. Tobin’s q is employed to represent firm value as in many prior studies (La Porta et al., 2002; Claessens et al., 2002; and Lemmon and Lins, 2003, among others). Tobin’s q is computed based on Chung and Pruitt (1994). 5 This method offers a number of advantages. First, the computational cost is low relative to other more complex methods of calculating Tobin’s q. Second, the data are readily available using COMPUSTAT for small, as well as large, firms. Finally, Chung and Pruitt (1994) and Perfect and Wiles (1994) find a high degree of correlation between the simple q calculation and more rigorous constructions of q. 6 DaDalt, Donaldson, and Garner (2003) note these three advantages of employing a simple construction of q and conclude that the simple q calculation is preferable in most empirical applications. To conduct a univariate analysis, we divide the sample into two groups based on Tobin’s q. The median Tobin’s q is used to split the sample. Then, we compare debt maturity between the two groups. Panel A of Table 3 shows the results of the univariate comparisons. The evidence reveals that, for the high­q group, 85.26% of total debt matures in 1 year or more. On the contrary, for the low­q group, 88.56% of total debt matures in 1 year or more. The difference is statistically significant at the 1% level or better. Hence, it appears that firms in the high­q group (more valuable firms) carry a smaller proportion of debt that matures in 1 year or more. Short­term debt seems to be associated with higher firm value. The same conclusion is obtained when we investigate the other debt maturities. For instance, 50.35% of total debt matures in 5 years or more for the high­q group whereas that proportion is 54.63% for the low­q group. Again, more valuable firms seem to carry more short­term debt (less long­term debt). This evidence is consistent across debt maturities from 1 to 5 years. In Panel B of Table 3, we show the correlation coefficients between Tobin’s q and the percentage of total debt that matures in 1 through 5 years or more. Evidently, all of the correlation coefficients are negative and statistically significant at the 1% level. The evidence here indicates that firm value is inversely related to the length of debt maturity, i.e. more valuable firms hold more short­term debt and less long­term debt. 4 Following Datta, Iskandar­Datta, and Raman (2005), we define debt maturity as the proportion of debt maturing in more than a certain number of years. 5 The q ratio is calculated as the following sum divided by book value of total assets: (market value of equity + liquidation value of preferred stock + the book values of long­term debt and current liabilities – current assets + book value of inventory). 6 Perfect and Wiles (1994) report that regression results using the simple approximation may differ from more complex estimations of Tobin’s q. However, when estimating relationships using changes in values, the simple approximation produces similar results to the other calculation of q. We conduct tests using both value levels and changes.
b. Regression Analysis The univariate results may be driven by firm­specific characteristics. As a result, we perform a multivariate regression analysis that explicitly takes into consideration firm­specific characteristics and time variation. Our regression analysis has Tobin’s q as the dependent variable. The independent variables include debt maturity and a number of control variables. The logarithm of total assets is utilized to control for firm size. Leverage is included as it may affect agency costs and firm value in several ways. First, 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. Obviously, profitability should be relevant to firm value. We utilize the ratio of EBITDA to total assets to proxy for profitability. Finally, we account for growth opportunities by using the book­to­market ratio. These are the typical control variables utilized in many previous studies. 7 Recognizing that our sample spans 32 years of data, we account for possible time variation by including year dummies in the regression analysis. The regression results are documented in Table 4. The dependent variable is Tobin’s q. Note that the coefficients of the debt maturity variables are negative and statistically significant in all of the regressions except for Model 5. Thus, the results indicate that firms with less long­term debt (more short­ term debt) are more valuable. Also note that all the R 2 ’s are more than 70%, which is remarkably high for a cross­sectional analysis. The empirical evidence is in agreement with the theoretical arguments that short maturity debt enhances firm value. Due to the cross­sectional time series nature of our dataset, it can be argued that panel regressions should be used rather than OLS. As a result, we run fixed­effects regressions to confirm the results. The fixed­effects approach helps control for unobservable firm characteristics. This approach alleviates the concern that the relationship between debt maturity and firm value may be spurious because of unobservable variables. For instance, it is conceivable that both firm value and debt maturity are related to unobservable firm­specific characteristics such as firm culture or management attitude. The fixed­effects method mitigates the possibility of a spurious relationship due to omitted variables (Carter, Rogers, and Simkins, 2006; Chi, 2005) Therefore, we run fixed­effects regressions as a robustness check and show part of the results in the Appendix. 8 We employ both firm and year fixed­effects. The results remain consistent and confirm the benefit of short­term debt. It can be argued that leverage and debt maturity are determined endogenously (Johnson, 2003; Datta et al., 2005). Including both leverage and debt maturity as independent variables might make the regression results biased (Barclay, Marx, and Smith, 1997). We cope with this potential concern in two ways. First, we exclude leverage as a control variable and re­estimate the regressions. We find that that the results remain similar even when leverage is not included. Second, we employ a two­stage analysis where we estimate leverage in the first stage and include the predicted value of leverage as a control variable in the second stage. 9 Again, the results remain consistent. The results thus appear to be robust. Furthermore, Barlay and Smith (1995) caution that debt maturity may be driven by industry. Hence, we industry­adjust all the variables and rerun the regressions. The industry adjustment is accomplished by computing the industry median for each variable based on the first 2 digits of the SIC, and then find the difference between the actual value and the industry median. We show part of the results in the Appendix. Even after controlling for possible industry effects, we still obtain similar results showing a positive association between short­term debt and firm value. 7 These variables are available throughout the whole sample period of 32 years. Including additional variables would reduce the sample size as most variables are not available for the entire sample period. 8 For conciseness, we show only the results for DEBT3 in the Appendix. Using any other maturity does not materially change the results. 9 We estimate leverage as a function of firm size and profitability in the first stage. An expanded model can be used but most variables are not available for the entire sample period, making it difficult to estimate many alternative models.
c. Potential Impact of Regulation It is our contention that debt maturity structure affects firm value through its impact on agency costs. Regulated firms may suffer less agency conflicts because regulation removes a certain degree of managerial discretion, making it less likely that managers take actions that benefit themselves at the expense of stockholders (Booth, Cornett, and Tehranian, 2002, and Kole and Lehn, 1997). Because regulation may already alleviate agency costs in regulated firms, the benefits of short­term debt in combating agency conflicts may be less necessary in these firms. In other words, there may be a substitution effect between regulation and short­term debt. As a result, we investigate regulated firms separately.
We identify 4,246 observations that are utility companies (SIC codes 4900­4999) and classify this group of firms as our regulated sample. Utilities are subject to a great deal of regulation. We then replicate the regression analysis conducted previously on this regulated sample. The results reveal that short­term debt is associated with higher firm value. 10 Hence, even in regulated firms where agency costs should be less severe, short maturity debt still exhibits a beneficial effect on firm value. Regulation does not appear to substitute for short­term debt in lessening agency costs. d. The Sarbanes­Oxley Act of 2002 The Sarbanes­Oxley Act was enacted on July 30, 2002 as a consequence of Congressional hearing conducted since the first admissions of fraudulent behavior made by Enron. President George W. Bush characterized this Act as “the most far­reaching reforms of American business practices since the time of Franklin D. Roosevelt.” 11 The Act introduces new provisions for management, directors, auditors and analysts, and significantly raises criminal penalties for securities fraud, for destroying, altering or fabricating records in federal investigations or any scheme or attempt to defraud shareholders. Evidently, this Act is intended to hold managers more accountable to shareholders. The increased accountability should bring manager and shareholder interests in better alignment, thereby alleviating agency costs. 12 It is conceivable that this diminution of agency problems may affect managers’ choice between short­ and long­term debt. Therefore, we predict that the enactment of the Sarbanes­Oxley Act may influence the association between debt maturity and firm value. As a result, we perform an empirical analysis pre­ and post­Sarbanes­Oxley. 13 Using 2002 as the cut­off, we classify observations from before 2002 as the pre­SOX sample. On the contrary, observations from 2002 and after are included in the post­SOX sample. Then, we conduct a regression analysis on each sample separately. For the pre­SOX sample, the results are similar to those reported earlier, i.e. a higher proportion of short­term debt is associated with higher firm value. Interestingly, however, debt maturity structure is not found to be related to firm value in the post­SOX sample. It appears that the beneficial effect of short­term debt vanishes after the enactment of SOX. 14 We conjecture that, due to stricter regulation on corporate governance post­SOX, the role of debt maturity in mitigating agency conflicts may be rendered less necessary. In other words, SOX may substitute for debt maturity in combating agency costs. Thus, the association between debt maturity structure and firm value is not found after the passage of SOX. e. Debt Maturity, Firm Value, and Agency Costs of Managerial Discretion So far, we have established that firms using more short­term debt exhibit higher firm value. In this section, we attempt to demonstrate why the use of short­term debt is associated with higher firm 10 Results are now shown but available upon request. Elizabeth Bumiller, “Bush Signs Bill aimed at Fraud in Corporations,” N.Y. Times, July 31, 2002. 12 Around the same time, the Securities Exchange Commission (SEC) collaborated with the major stock exchanges to develop a stricter set of exchange listing requirements for publicly traded firms. 13 The impact of Sarbanes­Oxley on debt maturity structure may come about through various mechanisms. For instance, more independent directors on the board may influence the likelihood of managers opportunistically using long­term debt to avoid frequent external monitoring by the capital markets. Regardless of the specific mechanisms, we argue that, in general, Sarbanes­Oxley is intended to alleviate agency costs and might affect debt maturity structure. 14 Results are not shown but available upon request.
11 value. Our focus is on the role of short­term debt in mitigating the agency costs of managerial discretion. Short­term debt has been argued to reduce agency costs by subjecting managers to more frequent monitoring by external parties. To the extent that short maturity debt enhances firm value by alleviating agency conflicts, it is expected that the beneficial effect of short­term debt should be more pronounced in firms where agency costs are more severe. On the contrary, in firms where agency problems are less serious, the role of short­term debt may be made superfluous or, at least, less necessary. In such firms, the association between the use of short­ term debt and firm value should be less strong. In summary, we posit that the diminution of agency costs of managerial discretion serves as a mechanism through which short­term debt increases firm value. To test the above supposition, we segregate the sample into two portfolios, one where agency costs are high, the other where agency problems are less severe. Jensen (1986) contends that firms with excess cash are more vulnerable to agency costs as managers are better able to exploit the excess cash for their own private benefits. On the basis of Jensen’s (1986) free cash flow hypothesis, several prior studies employ the amount of free cash flow to indicate the severity of potential agency costs. 15 Hence, we follow the same method and compute the ratio of free cash flow to total assets for the sample firms. 16 Then, we classify firms where the free cash flow ratio is above the sample median as more susceptible to agency conflicts. Those where the ratio is below the median are placed in the other portfolio, where agency costs are presumed less severe. In Table 5 Panel A, we replicate the previous regressions on the high free­cash­flow portfolio. The usual control variables are included but not shown in the table to conserve space. Please note in Table 5 that the coefficients of all the debt maturity variables (except DEBT3) are negative and significant. Thus, longer debt maturity is associated with lower firm value for the high FCF firms, suggesting that short­term debt is beneficial in these firms. In Table 5 Panel B, we repeat the same regressions on the portfolio of firms with low FCF. It is remarkable that none of the debt maturity variables exhibit a significant coefficient, implying no association between debt maturity and firm value. We argue that, because these low FCF firms suffer less from agency conflicts, the role of short­term debt in mitigating agency costs is less necessary. Thus, we cannot find any significant effect of debt maturity on firm value for these firms. f. Possible Endogeneity One critical problem that plagues empirical studies in corporate governance is endogeneity. If endogeneity were present, it would imply that adopting short­term debt does not necessarily increase firm value but high­value firms choose to adopt a higher degree of short maturity debt. Several methods have been employed to deal with endogeneity. For instance, a number of studies utilize simultaneous equations. This method may have a rigorous theoretical basis. However, it is very hard to implement this method effectively for many reasons. First, it is well known that it is nearly impossible to find variables that are truly exogenous to serve as instrumental variables. Second, the results generated by simultaneous equations are notoriously sensitive to the choice of instrumental variables, making the results difficult to interpret. Third, because we employ a large dataset that spans a lengthy period of time, it is nearly impossible to find instrumental variables that are available continuously for the entire sample period. Due to the above complications with simultaneous equations, we utilize an alternative method that can alleviate possible endogeneity, that is, examining changes in firm value relative to changes in debt maturity. This approach is easier to implement and is less susceptible to endogeneity. 17 Table 6 Panel A shows the regression results where the annual change in firm value is the dependent variable. The independent variables include changes in debt maturity. We also control for 15 There are other ways to account for agency conflicts. For instance, some studies use board composition or CEO compensation as a proxy for the extent of agency costs (for instance, more independent boards, less agency costs or better CEO compensation structure, less agency costs). However, data on boards and agency costs are available only in the 1990’s and 2000’s. Only the free cash flow ratio can be computed for the entire sample period going all the way back to the 1970’s. This is the primary reason why the free cash flow ratio is selected. 16 The free cash flow ratio is computed as the firm’ earnings plus depreciation minus capital expenditures, all divided by total assets. 17 Although this method does not completely rule out endogeneity, it does make it much more likely that causality runs from debt maturity to firm value than vice versa (See Carter, Rogers, and Simkins, 2006).
changes in total assets, leverage, profitability and the market­to­book ratio. As in previous analysis, we first restrict our sample to the high FCF portfolio. Since firms with high FCF should suffer more agency costs, we anticipate finding that a reduction in debt maturity (an increase in short­term debt) is associated with an increase in firm value for these firms. The results in Table 6 indicate that the coefficients of the changes in debt maturity are all negative and significant, lending support to our hypothesis. In Table 6 Panel B, the sample is restricted to only those firms with low FCF (low agency costs). The results in Table 7 Panel B reveal that none of the coefficients of the debt maturity variables are significant. As these firms do not incur severe agency costs, the role of short­term debt in reducing agency problems is less necessary. The empirical evidence is in agreement with this hypothesis. In conclusion, we find robust empirical evidence in favor of the beneficial effect of short­term debt usage when we investigate both the levels and the changes of debt maturity and firm value. g. Potential Limitation A large number of studies investigate the impact of a single corporate governance mechanism on firm value. For instance, firm performance has been related to ownership structure (Demsetz and Lehn, 1985; Morck, Shleifer, and Vishny, 1988; McConnell and Servaes, 1990; and Hermalin and Weisbach, 1991), to blockholders (Shleifer and Vishny, 1986; Admati, Pfleiderer and Zechner, 1994), to the board of directors (Hermalin and Weisbach, 1991; Byrd and Hickman, 1992; Rosenstein and Wyatt, 1990), and to executive compensation (Murphy, 1999), among others. This study closely follows this strand of the literature as we examine the role of short­term debt as a governance mechanism to mitigate agency costs and improve firm value. However, it can be argued that multiple corporate governance mechanisms can interact with one another (Agrawal and Knoeber, 1996). If this is the case, then, focusing on the impact of one governance mechanism on firm value might not be appropriate. We acknowledge that this is one potential limitation of this study. It would be ideal if we could include multiple governance mechanisms in this study and examine their effects in combination. However, data on other governance mechanisms are not available as far back as the 1970’s. For instance, data on the board of directors reported by the Investor Responsibility Research Center (IRRC) are available only starting from 1996. Likewise, executive compensation data are reported only from the early 1990’s. Data on anti­takeover provisions became available only in 1990. Blockholder data are available beginning only in the mid­1990’s. Thus, to analyze any other governance mechanisms along with debt maturity, we would have to shorten our sample period considerably, thereby discarding tens of thousands of observations. We argue, though, that the insights obtained from analyzing a substantial sample spanning across three decades compensate for a lack of analysis of other governance mechanisms. Furthermore, because we also use the individual­firm fixed­effects approach to confirm our results, the impact of possibly omitted governance variables should be minimized. CONCLUDING REMARKS Grounded in agency theory, this study seeks to ascertain the impact of debt maturity structure on firm value. Short maturity debt is hypothesized to alleviate agency costs in several ways (Myers, 1977; Rajan and Winton, 1995; Stulz, 2000). We surmise that a diminution in agency costs should result in higher firm value. Thus, firms employing shorter debt maturity should be more valuable. Utilizing a comprehensive data set encompassing more than 100, 000 observations over 32 years, we find empirical evidence consistent with the hypothesis. Furthermore, we contend that one mechanism through which short­term debt enhances firm value is by mitigating the agency costs of managerial discretion. Employing the amount of available free cash flow to represent the extent of likely agency conflicts, we document that the beneficial effect of short­ term debt is concentrated only in firms where agency problems are severe. In addition, we investigate changes in firm value with respect to changes in debt maturity structure and find consistent evidence. In summary, short­term debt enhances firm value. We show one specific way in which value enhancement is accomplished, a reduction in the agency costs of managerial discretion.
Table 1: Sample Distribution by Year Year Frequency Percent Cumulative Percent 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 Total 104 2,472 2,596 2,586 2,694 2,823 2,793 3,011 3,315 3,248 3,463 3,443 3,437 3,487 3,548 3,382 3,232 3,154 3,195 3,349 3,540 3,652 4,008 4,252 4,195 4,139 4,100 3,978 3,636 3,345 3,167 2,780 104,124 0.1 2.4 2.5 2.5 2.6 2.7 2.7 2.9 3.2 3.1 3.3 3.3 3.3 3.3 3.4 3.2 3.1 3.0 3.1 3.2 3.4 3.5 3.8 4.1 4.0 4.0 3.9 3.8 3.5 3.2 3.0 2.7 100.0
0.1 2.5 5.0 7.5 10.0 12.7 15.4 18.3 21.5 24.6 28.0 31.3 34.6 37.9 41.3 44.6 47.7 50.7 53.8 57.0 60.4 63.9 67.7 71.8 75.9 79.8 83.8 87.6 91.1 94.3 97.3 100.0 Table 2: Descriptive Statistics of Corporate Debt Maturity and Firm Characteristics Panel A: Descriptive Statistics of Corporate Debt Maturity The percent of total debt maturing from the fiscal year end is from COMPUSTAT. As in Datta et al. (2005), DEBT1­DEBT5 represent the percentages of total debt maturing in more than 1 through more than 5 years respectively. % of Debt that Matures in More than Mean S.D. 25 th Median 75 th 1 year (DEBT1) 86.91% 20.39% 85.71% 94.15% 98.26% 2 years (DEBT2) 75.14% 26.85% 65.95% 85.02% 94.30% 3 years (DEBT3) 66.00% 29.65% 48.07% 75.16% 89.37% 4 years (DEBT4) 58.84% 30.85% 35.61% 65.62% 84.01% 5 years (DEBT5) 52.49% 31.53% 26.98% 56.20% 78.30% Panel B: Summary Statistics of Firm Characteristics Tobin’s q is computed based on Chung and Pruitt (1994). Leverage is represented by long­term debt divided by total assets. The market­to­book ratio is calculated as the market value of equity divided by the book value of equity. Mean S.D. 25 th Median 75 th Sales 1,129.03 5,683.31 21.17 97.73 457.03 Total Assets 1,180.14 5,571.74 19.49 83.11 415.14 Tobin’s q 2.28 56.00 0.63 0.90 1.49 Market­to­Book Ratio 1.25 308.41 0.16 0.43 1.06 EBITDA/Total Assets ­5.79% 9.88% 4.21% 11.60% 17.16% Leverage 36.50% 314.90% 13.33% 27.60% 42.45% * ** *** statistically significant at the 10% level statistically significant at the 5% level statistically significant at the 1% level
Table 3: Univariate and Correlation Analysis The percent of total debt maturing from the fiscal year end is from COMPUSTAT. As in Datta et al. (2005), DEBT1­DEBT5 represent the percentages of total debt maturing in more than 1 through more than 5 years respectively. Panel A: Univariate Analysis % of Debt that Matures in More than High Tobin’s q Mean (Median) Low Tobin’s q Mean (Median) Difference 1 year (DEBT1) 85.26% (93.91%) 88.56% (94.32%) ­26.22*** 2 years (DEBT2) 72.95% (83.83%) 77.32% (85.82%) ­26.36*** 3 years (DEBT3) 63.74% (72.89%) 68.25% (76.66%) ­24.66*** 4 years (DEBT4) 56.73% (62.40%) 60.94% (67.75%) ­22.10*** 5 years (DEBT5) 50.35% (51.67%) 54.63% (59.38%) ­21.98*** t­statistics Panel B: Correlations between Tobin’s q and Debt Maturity Debt Maturing in More Than Tobin’s q (p­value) * ** *** 1 Year 2 Years 3 Years 4 Years 5 Years DEBT1 DEBT2 DEBT3 DEBT4 DEBT5 ­0.0386*** (0.00) ­0.0428*** (0.00) ­0.0527*** (0.00) ­0.0124*** (0.00) ­0.0309*** (0.00) statistically significant at the 10% level statistically significant at the 5% level statistically significant at the 1% level
Table 4: Regressions of Tobin’s q on Debt Maturity Tobin’s q is computed based on Chung and Pruitt (1994). Leverage is represented by long­term debt divided by total assets. The market­to­book ratio is calculated as the market value of equity divided by the book value of equity. Model (1) (2) (3) (4) (5) Intercept ­0.742 (­0.25) ­1.480 (­0.51) ­1.727 (­0.59) ­1.954 (­0.67) ­2.140 (­0.73) DEBT1 ­2.008*** (­4.26) ­ ­ ­ ­ DEBT2 ­ ­1.309*** (­3.62) ­ ­ ­ DEBT3 ­ ­ ­1.007*** (­3.09) ­ ­ DEBT4 ­ ­ ­ ­0.673** (­2.17) ­ DEBT5 ­ ­ ­ ­ ­0.354 (­1.18) Ln (Total Assets) ­0.197*** (­4.68) 0.199*** (­4.70) ­0.208*** (­4.94) ­0.222*** (­5.32) ­0.233*** (­5.66) Leverage 10.606*** (208.44) 10.606*** (208.40) 10.606*** (208.39) 10.606*** (208.37) 10.604*** (208.36) EBITDA/Total Assets ­1.633*** (­100.79) ­1.634*** (­100.82) ­1.634*** (­100.85) ­1.634*** (­100.88) ­1.635*** (­100.90) Market­to­Book Ratio ­0.001*** (­2.89) ­0.001*** (­2.89) ­0.001*** (­2.89) ­0.001*** (­2.89) ­0.001*** (­2.89) Yes Yes Yes Yes Yes Year Dummies Adjusted­R 2 F­statistics N * ** *** 72.2% 72.2% 72.2% 72.2% 72.2% 7,524.70*** 7,524.20*** 7,523.84*** 7,523.36*** 7,523,02*** 104,124 104,124 104,124 104,124 104,124 statistically significant at the 10% level statistically significant at the 5% level statistically significant at the 1% level
Table 5: Regressions of Tobin’s q on Debt Maturity (High vs. Low Free Cash Flow) Tobin’s q is computed based on Chung and Pruitt (1994). Leverage is represented by long­term debt divided by total assets. The market­to­book ratio is calculated as the market value of equity divided by the book value of equity. Panel A: High Free Cash Flow Model (1) (2) (3) (4) (5) Intercept 0.663 (1.40) 0.376 (0.80) 0.299 (0.63) 0.263 (0.56) 0.257 (0.54) DEBT1 ­0.473*** (­10.32) ­ ­ ­ ­ DEBT2 ­ ­0.124*** (­3.77) ­ ­ ­ DEBT3 ­ ­ 0.006 (0.19) ­ ­ DEBT4 ­ ­ ­ ­0.078*** (­2.87) ­ DEBT5 ­ ­ ­ ­ ­0.090*** (­3.45) Yes Yes Yes Yes Yes 12.9% 194.98*** 47,314 12.7% 192.04*** 47,314 12.7% 191.59*** 47,314 12.7% 191.86*** 47, 314 12.7% 191.97*** 47,314 Control variables included Adjusted­R 2 F­statistics N * ** *** statistically significant at the 10% level statistically significant at the 5% level statistically significant at the 1% level
Table 5 (Continued) Panel B: Low Free Cash Flow Model (1) (2) (3) (4) (5) Intercept ­0.929 (0.20) ­1.401 (­0.31) ­1.479 (0.33) ­1.670 (0.37) ­1.841 (­0.41) DEBT1 ­1.033 (­1.05) ­ ­ ­ ­ DEBT2 ­ 0.550 (­0.72) ­ ­ ­ DEBT3 ­ ­ 0.466 (0.67) ­ ­ DEBT4 ­ ­ ­0.206 (­0.31) ­ ­ DEBT5 Control variables included Adjusted­R 2 F­statistics N * ** *** ­ ­ ­ ­ 0.041 (0.06) Yes Yes Yes Yes Yes 72.7% 72.7% 72.7% 72.7% 72.7% 3,508.54*** 3508.48*** 3,508.48*** 3,508.44*** 3,508.43*** 47,313 47,313 47,313 47,313 47,313 statistically significant at the 10% level statistically significant at the 5% level statistically significant at the 1% level
Table 6: Regressions of ∆ Tobin’s q on ∆ Debt Maturity Tobin’s q is computed based on Chung and Pruitt (1994). Leverage is represented by long­term debt divided by total assets. The market­to­book ratio is calculated as the market value of equity divided by the book value of equity. Panel A: High Free Cash Flow Model (1) (2) (3) (4) (5) Intercept 0.162*** (4.11) 0.162*** (4.11) 0.162*** (4.11) 0.162*** (4.11) 0.162*** (4.11) ∆ DEBT1 ­156.095** (­2.09) ­ ­ ­ ­ ∆ DEBT2 ­ ­55.946** (­2.09) ­ ­ ­ ∆ DEBT3 ­ ­ ­32.214*** (­2.09) ­ ­ ∆ DEBT4 ­ ­ ­ ­25.132** (­2.09) ­ ∆ DEBT5 ­ ­ ­ ­ ­20.503** (­2.09) ∆ Ln (Total Assets) ­0.838*** (­24.29) ­0.838*** (­24.29) ­0.838*** (­24.29) ­0.838*** ­0.838*** (­24.29) (­24.29) ∆ Leverage 3.700*** (59.78) 3.700*** (59.78) 3.700*** (59.78) 3.700*** (59.78) ∆ (EBITDA/Total Assets) ­1.787*** (­37.88) ­1.787*** (­37.88) ­1.787*** (­37.88) ­1.787*** ­1.787*** (­37.88) (­37.88) 0.000** (­2.32) 0.000** (­2.32) 0.000** (­2.32) 0.000** (­2.32) 0.000** (­2.32) Yes Yes Yes Yes Yes ∆ Market­to­Book Ratio Year Dummies Adjusted­R 2 F­statistics N * ** *** 3.700*** (59.78) 16.2% 16.2% 16.2% 16.2% 16.2% 213.80*** 213.80*** 213.80*** 213.80*** 213.80*** 38,597 38,597 38,597 38,597 38,597 statistically significant at the 10% level; statistically significant at the 5% level; statistically significant at the 1% level
Table 6 (Continued) Panel B: Low Free Cash Flow Model (1) (2) (3) (4) (5) Intercept ­0.456 (­0.46) ­0.456 (­0.46) ­0.456 (­0.46) ­0.456 (­0.46) ­0.456 (­0.46) ∆ DEBT1 ­278.997 (0.44) ­ ­ ­ ­ ∆ DEBT2 ­ ­123.28 (­0.48) ­ ­ ­ ∆ DEBT3 ­ ­ ­83.580 (­0.50) ­ ­ ∆ DEBT4 ­ ­ ­ ­72.730 (­0.52) ­ ∆ DEBT5 ­ ­ ­ ­ ­69.00 (­0.55) ∆ Ln (Total Assets) ­4.565*** (­8.96) ­4.567*** (­8.96) ­4.568*** (­8.96) ­4.569*** (­8.96) ­4.570*** (­8.96) ∆ Leverage 10.787*** (153.67) 10.787*** (153.67) 10.787*** (153.67) 10.787*** (153.67) 10.787*** (153.67) ∆ (EBITDA/Total Assets) ­1.618*** (­73.43) ­1.618*** (­73.43) ­1.618*** (73.43) ­1.618*** (­73.43) ­1.618*** (­73.43) ∆ Market­to­Book Ratio ­0.001*** (­2.76) 0.001*** (­2.76) ­0.001*** (­2.76) ­0.001*** (­2.76) ­0.001*** (­2.76) Yes Yes Yes Yes Yes Year Dummies Adjusted­R 2 F­statistics N * ** *** 80.8% 80.8% 80.8% 80.8% 80.8% 4,302.80*** 4,302.81*** 4,302.81*** 4,302.82*** 4,302.82*** 35,812 35,812 35,812 35,812 35,812 statistically significant at the 10% level statistically significant at the 5% level statistically significant at the 1% level
Appendix Table A1: Regressions of Tobin’s q on Debt Maturity (Fixed­effects and Industry­ adjusted) Tobin’s q is computed based on Chung and Pruitt (1994). Leverage is represented by long­term debt divided by total assets. The market­to­book ratio is calculated as the market value of equity divided by the book value of equity. Model (1) (2) Fixed­Effects Industry­Adjusted Intercept ­ 1.761* (1.89) DEBT3 ­1.722*** (­4.78) ­2.141* (­1.70) 0.023 (0.17) ­0.171*** (­3.90) Leverage 11.44*** (215.18) 10.623*** (208.88) EBITDA/Total Assets ­1.333*** (­80.64) ­1.630*** (­100.62) Market­to­Book Ratio 0.001*** (2.89) ­0.001*** (­2.90) 72.12% 60,082.2*** 104,086 72.2% 54,215.65*** 104,124 Ln (Total Assets) Adjusted­R 2 F­statistics N * ** *** statistically significant at the 10% level statistically significant at the 5% level statistically significant at the 1% level
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