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Do defaulting CEOs and directors increase the likelihood of financial distress of the firm?

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Abstract

We hypothesize that the information on a CEO’s and directors’ (board members) past personal payment default entries in public credit data files significantly increases the predictive power of Altman’s (in J Fin 23(4):589–609, 1968) and Ohlson’s (In J Acc Res 18(1):109–131, 1980) distress prediction models. We base our hypothesis on the literature showing that (1) managerial traits such as overconfidence, over-optimism, and the illusion of control affect corporate decisions and that (2) these same personal traits explain personal over-indebtedness and credit defaults. Our results of analyzing the credit data files of more than 100,000 CEOs and directors of the Finnish private limited liability companies support this hypothesis. Our results remain materially unchanged when using the bootstrapping method to assess their significance and when excluding small firms (firm size below the sample median). Collectively, our results imply that creditors should recognize the increased distress risk of firms appointing defaulting CEOs and directors.

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Notes

  1. The term financial distress refers to financial straits that may lead to the juridical bankruptcy of the firm. Firms in financial trouble may renegotiate their loans, restructure their business by, for example, selling off part of the business or committing to other actions needed to avoid bankruptcy. Typically, all these actions are more or less costly for creditors. In our study, we measure financial distress by filings for insolvency and bankruptcy.

  2. Our discussion with the Finnish credit bureau Suomen Asiakastieto Ltd. implied that, while personal credit defaults are routinely checked when granting personal credit, this practice is not common when granting corporate loans and appointing CEOs or directors.

  3. We use private (nonlisted) rather than public (listed) firms, because only two public Finnish firms went bankrupt during the sample period.

  4. For recent review articles in the area, see Shefrin (2010) and Baker et al. (2007).

  5. Kilborn (2002) even states that ‘The overconfidence bias figures prominently in the history of consumer credit in the United States.’

  6. Distress prediction models based on financial ratios generally focus on the profitability, cash flow generation, financial leverage, and liquidity of the firm.

  7. The Finnish Companies Act, which is in accordance with the European Union directives, greatly emphasizes a board’s role in the governance structure of the firm. Specifically, directors have a legal responsibility to actively assess all the actions taken by the firm on a continuous basis. In the Finnish Corporate Governance Code, the list of directors’ duties is very similar to those described by various professional organizations in the US. (See, for example, the Committee on Corporate Laws’ Corporate Director’s Guidebook, 2004.) While executives have a key role in the daily operations of the firm, the legislation therefore also creates incentives for directors to attend to the decision-making.

  8. Although anyone can easily retrieve (purchase) a given person’s payment default entries from a credit database, the Personal Data Act does not allow anyone to build up a database of her own by retrieving credit default entries on many people. However, Suomen Asiakastieto Ltd. provides credit default data for academic research upon request. This can be done because they preserve directors’ and CEOs’ anonymity by replacing their names with a specific code in the credit default database. They also replace directors’ and CEOs’ names in the financial statement database by the same code so that the credit default and financial statement data can be merged. Previous studies using these data include Eisenberg et al. (1998), Back (2005) and Laitinen and Laitinen (2009).

  9. Although payment defaults can be kept on publicly available records only for the periods described in Sect. 3.1., that is, for 2 through 5 years, the credit bureau can maintain historical records for internal use. These historical records are also available for academic research, because an individual’s default history cannot be traced from the records as described in footnote 8. Therefore, we could use the historical default data since 2001 in our analyses. To ensure that our distress prediction models are based on the information that was available before the bankruptcy or insolvency filings, we use only those past defaults of CEOs and directors that really were publicly available in the records in the end of 2005 (2006) given the type of the default described in Section 3.1. For instance, our distress prediction models containing financial ratios from the fiscal year 2005 include payment defaults that were kept in the records for previous 2 through 5 years depending on the type of the default.

  10. We exclude very small firms, that is, firms having annual sales less than 100,000 euros. The results of our empirical analyses using only those firms with sales greater than the sample median are qualitatively similar to those reported in the tables. (see Sect. 4.3).

  11. This proportion is roughly equal to that of the entire Finnish population.

  12. We have also estimated all our models by varying the minimum lag from one month to 11 months. These results are qualitatively similar to those reported in tables.

  13. Since our sample contains nonlisted firms, we cannot use other market-based variables such as those based on the Merton (1974) option model or the Black–Scholes-Merton option-pricing model (e.g., Hillegeist et al. 2004; Shumway 2001).

  14. The results reported in Tables 4 and 5 are based on the total sample. We obtain similar results when estimating the models for the randomly selected sub-sample containing half of the observations, which we use as an estimation sample in the out-of-the-sample analyses in Tables 6 through 8.

  15. All our results of comparing the four distress prediction models are qualitatively similar regardless of whether we use the decision rule or the logistic function to estimate the predicted likelihood of financial distress. However, consistent with the miscalibration argument, the predicted probabilities based on logistic function are greater than the actual distress rates.

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Acknowledgments

We gratefully acknowledge the useful comments provided by an anonymous referee, and the editor, Patricia Dechow. We also thank Liz Demers, Jennifer Francis, Henry Jarva, Peter Jennegren, Mirjam Lehenkari, Joshua Livnat, Henrik Nilsson, Per Olsson, Mikko Puhakka, Petri Sahlström, Hanna Setterberg, and Kent Skogsvik. We also thank the seminar participants at the 2010 Summer Accounting Research Conference at the Stockholm School of Economics (Sweden), the 2010 Nordic Conference on Financial Accounting at the Copenhagen Business School (Denmark), and the University of Oulu Accounting Research Seminar (Finland). We thank Suomen Asiakastieto Ltd. for providing the data needed in this study.

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  1. Department of Accounting, University of Oulu, P.O. Box 4600, 90014, Oulu, Finland

    Juha-Pekka Kallunki

  2. European Credit Research Institute at the Centre for European Policy Studies, Place du Congres 1, 1000, Brussels, Belgium

    Elina Pyykkö

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  1. Juha-Pekka Kallunki
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  2. Elina Pyykkö
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Correspondence to Juha-Pekka Kallunki.

Appendix

Appendix

See Table 9.

Table 9 Variables used in the empirical analyses
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Kallunki, JP., Pyykkö, E. Do defaulting CEOs and directors increase the likelihood of financial distress of the firm?. Rev Account Stud 18, 228–260 (2013). https://doi.org/10.1007/s11142-012-9203-x

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