In this study, we present that the behavior of earnings management by managers generally influences the debt maturity structure choice of corporations. The previous
literature of finance has supplied different theories to explain the determinants of debt maturity structure. We extend the concept of discrepancy of interests between managers and outside potential investors, and investigate whether the behavior of misleading outside investors impacts on the choice of debt issuing later. Previous studies about the impact of earnings management emphasize the relation between it and corporations’ stock performance. We reason that debt maturity choice is also influenced by earnings management. Corporations which mislead investors’ judgment about their quality have the incentive to lengthen their corporate debt maturity to avoid higher issuing costs in the future.
Using IPO firms as the sample, we show that corporations of aggressive activities in earnings management choose a larger portion of long-maturity debt. It is substantial to note that we combine the theory of earnings management with the factors influencing corporate debt maturity choice. Managers tend to concern the adequate debt maturity choice subsequently after they use earnings management to mislead outside investors’ judgment about corporations’ quality. The results demonstrate earnings management of aggressive firms in the IPO process brings about the higher proportion of long-maturity debt hereafter.
It is needed to note that we use only the discretionary current accruals of the IPO year, year 0, to explain the debt maturity structure choice of the next year, year +1. If managers tend to continue their behavior of earnings management, the discretionary current accruals in the year +1 probably also impact on the choice of debt maturity structure. Besides, we use the IPO firms as the sample because the behavior of earnings management apparently occurs in IPO process. It is believed that managers have different reasons to manipulate the reported earnings. We are hopeful that future research will provide more detailed and stable results which may explain the relation between debt maturity choice and earnings management from other dimensions.
References
Barclay, M. J., and C. W. Smith Jr., (1995), “The Maturity Structure of Corporate Debt,” Journal of Finance 50, 609-631.
Barclay, M. J., L. M. Marx, and C.W. Smith Jr., (1997), “Leverage and Maturity as Strategic Complements,” working paper, University of Rochester.
Berger, Allen N., Marco A. Espinosa-Vega, W. Scott Frame, and Nathan H. Miller, (2005), “Debt Maturity, Risk, and Asymmetric Information,” Journal of Finance 60, 2895-2923.
Brick, Ivan E., and S. Abraham Ravid, (1985), “On the Relevance of Debt Maturity Structure,” Journal of Finance 40, 1423-1437.
Brick, Ivan E., and S. Abraham Ravid, (1991), “Interest Rate Uncertainty and the Optimal Debt Maturity Structure,” Journal of Financial and Quantitative Analysis 26, 63-81.
Datta, Sudip, Mai Iskandar-Datta, and Kartik Raman, (2005), “Managerial Stock Ownership and the Maturity Structure of Corporate Debt,” Journal of Finance 60, 2333-2350.
Dechow, Patricia M., Richard G. Sloan, and Amy P. Sweeney, (1995), “Detecting Earnings Management,” The Accounting Review 70, 193-225.
Diamond, Douglas W., (1991), “Debt Maturity Structure and Liquidity Risk,”
Quarterly Journal of Economics 106, 709-737.
Flannery, Mark J., (1986), “Asymmetric Information and Risky Debt Maturity Choice,” Journal of Finance 41, 19-37.
Guedes, Jose, and Tim Opler, (1996), “The Determinants of the Maturity of Corporate Debt Issues,” Journal of Finance 51, 1809-1833.
Healy, Paul M., and James M. Wahlen, (1999), “A Review of the Earnings Management Literature and Its Implications for Standard Setting,” Accounting
Horizons 13, 365-383.
Johnson, Shane A., (2003), “Debt Maturity and the Effects of Growth Opportunities and Liquidity Risk on Leverage,” Review of Financial Studies 16, 209-236.
Jones, Jennifer J., (1991), “Earnings Management During Import Relief Investigations,” Journal of Accounting Research 29, 193-228.
Lewis, Craig M., (1990), “A Multiperiod Theory of Corporate Financial Policy Under Taxation,” Journal of Financial and Quantitative Analysis 25, 25-43.
Morris, James R., (1976a), “On Corporate Debt Maturity Strategies,” Journal of Finance 31, 29-37.
Morris, James R., (1976b), “A Model for Corporate Debt Maturity Decisions,”
Journal of Financial and Quantitative Analysis 11, 339-357.
Myers, Stewart C., (1977), “Determinants of Corporate Borrowing,” Journal of Financial Economics 5, 147-175.
Rangan, Srinivasan, (1998), “Earnings Management and the Performance of Seasoned Equity Offerings,” Journal of Financial Economics 50, 101-122.
Smith, C.W., Jr., (1986), “Investment Banking and the Capital Acquisition Process,”
Journal of Financial Economics 15, 3-29.
Stohs, Mark Hoven, and David C. Mauer, (1996), “The Determinants of Corporate Debt Maturity Structure,” Journal of Business 69, 279-312.
Teoh, Siew Hong, Ivo Welch, and T. J. Wong, (1998a), “Earnings Management and the Long-Run Market Performance of Initial Public Offerings,” Journal of Finance 53, 1935-1974.
Teoh, Siew Hong, Ivo Welch, and T. J. Wong, (1998b), “Earnings Management and the Underperformance of Seasoned Equity Offerings,” Journal of Financial Economics 50, 63-99.
Table I
Statistics for the Percentage of Long-term Debt That Matures in More Than One, Two, Three, Four, and Five Years from the Fiscal Year-End
The sample consists of 1,746 firms, including 873 IPO firms and 873 comparative non-IPO firms with SIC code between 2000 and 5999, in the period from 1991 through 2003. The sample firms must also have sufficient COMPUSTAT data to calculate discretionary current accruals in fiscal year 0. The data of long-term debt is also from COMPUSTAT.
Panel A. IPO Firms Percentage of Debt That
Matures in More Than
Mean Standard Deviation 25th Percentile Median 75th Percentile
One year Panel B. Non-IPO Firms
Percentage of Debt That Matures in More Than
Mean Standard Deviation 25th Percentile Median 75th Percentile
One year
Table II
Characteristics of Sample
The sample consists of 873 IPO firms which go public in the period from 1991 through 2003 with SIC code between 1991 and 5999. The sample firms must also have sufficient COMPUSTAT data to calculate discretionary current accruals in fiscal year 0. Panel A reports time distribution of the sample by IPO calendar year, and Panel B reports SIC distribution of the sample by two-digit SIC code.
Panel A. Time Distribution
Fiscal Year End Frequency Percentage (%)
1991
Table II (Continued)
Panel B. SIC Distribution
Industry Two-digit SIC Codes Frequency %
Oil and Gas Food Products
Paper and Paper Products Chemical Products Manufacturing
Computer Hardware & software Electronic Equipment
Transportation Scientific Instruments Communications
Electric and Gas Services Durable Goods
Retail
Eating and Drinking Establishments All Others
Table III
Descriptive Statistics of Sample
The sample consists of 830 IPO firms which go public in the period from 1991 through 2003 with SIC code between 2000 and 5999. Discretionary current accruals (DCA) are calculated by a two-digit SIC industry cross-sectional modified Jones (1991) model. Panel A shows summary statistics of DCA and debt maturity structure of the sample.
DCA is used to measure the extent of earnings management. Panel B shows the descriptive statistics of other exogenous we mention in this paper. The exogenous variables are also calculated from the items of COMPUSTAT. Firm Value is defined as the market value of total assets. The market value of total assets is calculated as (book value of total assets + market value of equity – book value of equity). M/B ratio is the ratio of firm value of total assets to book value of that. Abnormal Earnings is defined as (earnings in year t+1 – earnings in year t) / market value of equity in year t. Assets Maturity is already defined in the equation (3.3.5). Tax rate is defined as (tax income expense / pretax income). Leverage is defined as (total long-term debt / market value of total assets). Fixed Asset ratio is defined as (net property, plant, and equipment / book value of total assets). Profitability is defined as (operating income before depreciation / book value of total assets). Panel C reports the Pearson correlations of exogenous variables and p-value is reported in parentheses. * indicate significance at the 5% level.
Panel A. Summary Statistics of debt maturity structure by DCA Quartiles (1) 830 IPO Firms
DCA (%) Debt Maturity Structure (%)
Units Mean Median Standard Dev. Mean (DEBT3) Median
(DEBT3)
Mean (DEBT5) Median (DEBT5)
Conservative Q1 (DCA<-4.7%) 207 -17.83984 -10.99692 16.88148 41.16244 35.50638 21.73723 5.43572
Quartile 2 (-4.7 %< DCA<1.2%) 208 -1.36577 -1.18094 1.60230 53.28712 56.91463 33.01489 22.47770
Quartile 3 (1.2 %< DCA<9.9%) 208 4.99594 4.85501 2.52254 50.56178 56.46644 30.24775 18.63081
Aggressive Q4 (9.9%<DCA) 207 28.12679 21.75780 18.79094 39.86916 34.97405 23.74578 7.00549
All firms 830 3.4753 1.1915 20.7951 46.23387 46.20306 27.19712 12.43985
Panel B. Descriptive Statistics of Exogenous Variables (1) 830 IPO Firms
Observations Mean Standard Dev. 25th Percentile Median 75th Percentile
M/B
DCA (%) Debt Maturity Structure (%)
Units Mean Median Standard Dev. Mean (DEBT3) Median
(DEBT3)
Mean (DEBT5) Median (DEBT5)
Conservative Q1 (DCA<-5.1%) 101 -19.62155 -11.89515 16.53800 41.67476 36.34776 21.42587 5.58005
Quartile 2 (-5.1 %< DCA<0.55%) 101 -2.16611 -2.07817 1.62124 50.14048 49.66333 30.92872 19.48283
Quartile 3 (0.55 %< DCA<8.7%) 101 4.30075 4.51733 2.55307 52.29002 57.26691 33.05504 17.25817
Aggressive Q4 (8.7%<DCA) 101 27.53433 19.82392 19.74368 40.93936 36.43973 25.47186 10.95068
All firms 404 2.5119 0.5657 21.2802 46.26116 45.28905 27.72037 13.60383
Table III (Continued)
(2) 404 IPO Firms
Observations Mean Standard Dev. 25th Percentile Median 75th Percentile
M/B
Table III (Continued)
Panel C. Pearson Correlations Growth
Option
Firm Size Firm Quality Assets Maturity
Tax rate Term structure
DCA Leverage Profitability Fixed assets ratio Firm Quality 0.05257
(0.2918)
Table IV
Ordinary Least Squares Regression Estimating the Determinants of Debt Maturity
The table shows the regression results from an ordinary least squares regression. In Panel A, the percentage of long-term debt that matures in more than five years (DEBT5) is regressed on discretionary current accruals of the firm in IPO’s year, the firms’ market-to-book ratio, the natural log of firm value, the firm’s future abnormal earnings, the firm’s assets maturity, the firm’s tax rate, the risk-free term structure, and a dummy variable for firms in regulation industries. The single-equation regression is as follows:
Firm Size Abnormal Earnings AssetsMaturity Tax rate Term Structure Regulation dummy
β β β β β
We alter the dependent variable from DEBT5 to DEBT4 for robustness checking. The sample contains 404 observations which have available data for all variables. White’s (1980) heteroskedasticity consistent t-statistics are reported in parentheses. ***, **, and * indicate significance at the 1%, 5%, and 10% levels each.
Panel A. Dependent Variable: DEBT5
Independent Variables Predicted Sign OLS
Intercept
Table IV (Continued)
Panel B. Dependent Variable: DEBT4
Independent Variables Predicted Sign OLS
Intercept
Table V
Two-stage Regression Coefficients Explaining the Percentage of Total Long-term Debt That Matures in More Than 5 Years
This table shows the results of the second-stage regressions from a two-stage regression analysis. In Panel A, the explanatory variable for the second-stage regression is the percentage of total long-term debt that matures in more than 5 years (DEBT5). The predicted leverage is obtained form the first-stage regression where leverage is defined as the dependent variable. Panel B reports the other second-stage regression where the explanatory variable is leverage. White’s (1980) heteroskedasticity consistent t-statistics are reported in parentheses. ***, **, and * indicate significance at the 1%, 5%, and 10% levels each. The regressions are as follows:
2
Firm Size Abnormal Earnings Term Structure Leverage
Leverage DEBT M B Firm Size Fixed Assets Ratio
Profitability Abnormal Earnings ITC dummy Regulation dummy DEBT5 are regressed on all other exogenous variables.
Panel A. Dependent Variable: DEBT5
Independent Variables Predicted Sign 2SLS
Intercept
Table V (Continued)
Panel B. Dependent Variable: Leverage
Independent Variables Predicted Sign 2SLS
Intercept
DEBT5 (predicted)
Market-to-book ratio
Firm size
Fixed Assets Ratio
Profitability
Abnormal earnings
Investment tax credit dummy
Regulation dummy
／
＋
－
／
＋
／
＋
－
＋
0.132025 (4.87)***
0.411294 (3.53)***
-0.02908 (-5.48)***
-0.00901 (-1.29) 0.065239
(1.88)*
0.002384 (0.09) 0.000094
(0.01) -0.05457 (-2.04)**
0.002641 (0.09)
Adjusted R2
Number of observation
0.21626 404
Table VI Robustness Checks
The table shows the robustness checks for above two-stage least squares regression analysis. The dependent variable in this table is the percentage of total long-term debt that matures in more than four years (DEBT4). The definition of Leverage1 is the ratio of total long-term debt to estimated market value of assets and the definition of Leverage2 is the ratio of total debt to estimated market value of assets. Two equations of the regressions are as follows:
2
Firm Size Abnormal Earnings Term Structure Leverage
Firm Size Abnormal Earnings Term Structure Leverage
Independent Variables Predicted Sign 2SLS 2SLS
Intercept