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Corporate governance and default risk of firms cited in the SEC’s Accounting and Auditing Enforcement Releases

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Abstract

We examine the relationship between corporate governance and default risk for a sample of firms cited in the Securities and Exchange Commission’s Accounting and Auditing Enforcement Releases (AAERs). Using hazard analysis of actual default incidence and OLS regressions of a continuous variable capturing a firm’s “closeness to default,” we document changes in the relationships between various governance characteristics and default risk from the pre-AAER period to the post-AAER period. Specifically, smaller board size, greater board independence, greater gender diversity of the board, and lower concentration of institutional ownership are all shown to have a more favorable effect on lowering default risk in the post-AAER period relative to the pre-AAER period. Our comparative analysis of a group of firms with accounting restatements (but not cited in the AAERs) does not show similar changes in the relationships between the various corporate governance characteristics and default risk from the pre-restatement to the post-restatement period. This suggests that the regulatory sanctions experienced by AAER firms may have prompted creditor reevaluation of the firms’ information environment and the perceived efficacy of various corporate governance mechanisms in mitigating default risk.

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Notes

  1. AAERs describe the results of SEC investigations of financial reporting violations in the form of intentional material misstatements of financial numbers.

  2. As discussed in detail in Sect. 3, this variable is based on the structural default model of Merton (1974) and estimated following Hillegeist et al. (2004).

  3. There have also been studies examining the relationship between corporate governance and financial distress in non-US settings. See, for example, Lee and Yeh (2004) and Chen (2008).

  4. In addition, the sample period in Agrawal et al. (1999) is 1981–1992, when the corporate governance and financial reporting landscapes were not yet affected by subsequent legislative changes such as the Private Securities Litigation Reform Act of 1995 and the Sarbanes–Oxley Act of 2002.

  5. Fich and Slezak (2008) use two measures of distress: Altman’s Z-score and the interest coverage ratio. A firm is classified as distressed if its distress measure is below a critical value.

  6. It is worth noting that default risk and governance structures can both change in the post-AAER period. Farber (2005) documents a greater proportion of outside directors on the board for fraud firms cited in AAERs. This might have been prompted by AAER firms’ efforts to improve information transparency. In the post-AAER period, if the inherent statistical relationship between default risk and a particular governance mechanism remains the same and the reduction of default risk mainly results from the improved governance mechanism (which leads to a change in the value of that governance covariate, and in turn, a change in the dependent variable, default risk), the coefficient on the interaction term will be insignificant. Only when there is a change in the effectiveness of a governance mechanism in the post-AAER period will such a coefficient become significant.

  7. The discrete-time hazard model proposed by Shumway (2001) is dynamic in nature and captures changes in firm characteristics over time. The dynamic hazard model is computationally convenient in that its likelihood function is equivalent to that of a multi-period logit model with modified standard errors. This model has recently been used, for example, by Chava and Jarrow (2004), Beaver et al. (2005), Duffie et al. (2007), and Campbell et al. (2008) to study business failures.

  8. We obtain the bankruptcy and default information from multiple sources including Bankruptcy Data Source, Bankruptcy Yearbook and Almanac, Moody’s Corporate Default Risk Service, and Lynn Lopucki’s Bankruptcy Research Database. We also use Compustat to supplement the bankruptcy data as follows. Footnote information (AFTNT33, AFTNT34 and AFTNT35) in Compustat provides the month, year, and reasons of deletion of a firm. Code 2 under AFTNT35 denotes bankruptcy under Chapter 11, while Code 3 indicates bankruptcy under Chapter 7.

  9. We select a set of corporate governance variables that have been shown by prior studies (e.g., Bhojraj and Sengupta 2003; Ashbaugh-Skaife et al. 2006; Fich and Slezak 2008) to have a potential impact on default risk as well as governance variables that have been commonly included in the corporate governance literature using a more general setting. Our goal is to include as many relevant governance variables as possible without over-fitting the model for a relatively small AAER sample.

  10. Specifically, an affiliated director is defined as one who is a former employee, an employee of an affiliate of which the company owns less than 50 %, a service provider, a supplier, a customer, a recipient of charitable funds, an interlocking or designated director, or a family member of a director or executive.

  11. See Romano (1996) and Hermalin and Weisbach (2003) for a detailed literature review and discussion on the relationship between firm performance and board independence.

  12. Prior studies (Beasley 1996; Dechow et al. 1996; Agrawal and Chadha 2005) provide inconclusive evidence on whether CEO entrenchment itself can exacerbate the information asymmetry problem, leading to a greater chance of accounting irregularities.

  13. It is important to control for leverage, since accounting irregularity issues can alter a firm’s external financing choices (Chen et al. 2013), which include the use of debt capital.

  14. Book-to-market ratio and stock return volatility are also common proxies for a firm’s information environment and cost of monitoring, which can influence the choice and effectiveness of a firm’s governance mechanisms.

  15. We choose to focus on the S&P 1,500 firms for several reasons. First, S&P 1,500 firms typically receive closer public scrutiny than a randomly selected sample of firms. Since public scrutiny can serve as an implicit governance mechanism, this would help control for the effect of such a mechanism on default risk. Second, it allows us to obtain consistent data from RiskMetrics for the earlier years for which proxy statements are harder to obtain. Finally, many well-cited corporate governance studies are based on S&P 1,500 firms (e.g., Gompers et al. 2003; Adams and Ferreira 2009); and hence, our results can be contrasted with the findings of these studies.

  16. http://www.sec.gov/divisions/enforce/friactions.shtml.

  17. Unlike some other studies that use a broader definition of financial misrepresentation (e.g., Karpoff et al. 2008), we confine our data collection to AAERs in order to ensure the consistency and homogeneity of the events of interest. Our sample selection criteria is consistent with prior studies (e.g., Dechow et al. 1996; Beneish 1999; Farber 2005; Dechow et al. 2011) that investigate accounting frauds and use AAERs to identify frauds and egregious accounting misstatements. Because we focus solely on firms that have undergone significant changes in their information environment due to their accounting misstatements being publicized through certain regulatory actions (i.e., AAERs), frauds that have not been discovered (but can be potentially identified by researchers using predication tools such as abnormal accrual analysis) fall outside the scope of this study. To the extent that a fraud is not yet discovered by the market, holding everything else constant, the perceived information asymmetry of the firm would barely change. In turn, the effectiveness of corporate governance mechanisms on bankruptcy risk would also stay more or less the same.

  18. We only utilize the data from the previous year to replace the missing values in order to minimize measurement errors, which could be a sensitive issue for AAER firms given the potentially drastic changes in financial and governance characteristics around the AAER announcements.

  19. For example, if a firm has a fiscal year end of December 31 in 2011 and usually holds its shareholder meeting in March, the corporate governance variables are determined by the voting results at the annual shareholder meeting held in March 2011. In other words, the dependent variable, which is measured at December 31, 2011, is regressed on the governance mechanisms in place between March 2011 and March 2012.

  20. Given the limitations of the GAO restatement database, we also use an alternative restatement database, Audit Analytics, to verify our findings in Table 7. The results based on Audit Analytics are similar to those based on the GAO data: restatement firms do not experience the same types of significant changes in the relationship between corporate governance and default risk in the post-restatement period.

  21. Interdisciplinary research drawing on extant political science literature could be a fruitful direction in the development of such a theory. See, for example, Carpenter et al. 2007.

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Acknowledgments

The authors would like to thank an anonymous referee and the editor for valuable comments and helpful suggestions. We also greatly appreciate the summer research support provided by the Milgard School of Business, University of Washington Tacoma.

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  1. Milgard School of Business, University of Washington Tacoma, 1900 Commerce Street, Campus Box 358420, Tacoma, WA, 98402-3100, USA

    Zhiyan Cao, Fei Leng, Ehsan H. Feroz & Sergio V. Davalos

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  1. Zhiyan Cao
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  2. Fei Leng
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  3. Ehsan H. Feroz
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Correspondence to Zhiyan Cao.

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Cao, Z., Leng, F., Feroz, E.H. et al. Corporate governance and default risk of firms cited in the SEC’s Accounting and Auditing Enforcement Releases. Rev Quant Finan Acc 44, 113–138 (2015). https://doi.org/10.1007/s11156-013-0401-9

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