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From distress to exit: determinants of the time to exit

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Abstract

This paper analyses the duration of the time to exit of distressed firms, differentiating between court driven exits (mainly bankruptcies) and voluntary liquidations. It examines how long firms survive after initial signs of economic distress. The study is conducted on an extensive dataset of 5,233 Belgian distress-related exits of mature firms, the majority being privately held. The results highlight that slack resources have an opposite effect on the timing of court driven exits and voluntary liquidations. On the one hand, high levels of available and potential slack increase the time to court driven exit, as they allow distressed firms to postpone an impending court driven exit. On the other hand, high available slack resources shorten the time to voluntary liquidation, since they make voluntary liquidation easier. Further, a high level of stakeholder dependence increases the time to exit after distress, whether the firm exits through voluntary liquidation or through a court decided exit. This is explained by the fact that stakeholder dependence increases the complexity of the exit decision and the exit procedure.

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Notes

  1. The unpublished empirical study of Balcaen et al. (2009) is largely based on the same dataset of distress-related exits as the one used in the current study, but the research question and methodology differs. This paper investigates the determinants of the exit type after distress and uses nested logit models to distinguish between court driven exits, voluntary liquidations and restructuring exits in the form of a takeover, merger or split.

  2. We do not investigate firms that exit through takeover or merger, due to the low incidence of these exits after distress. In addition, these exits involve distinct dynamics, as compared to voluntary liquidations and bankruptcies (Balcaen et al. 2009).

  3. Organizational slack may also benefit healthy firms (Galbraith 1973). Within certain limits, it may increase competitive advantage and lead to a higher performance (Pfeffer and Salancik 1978; Hambrick and D’Aveni 1988; Singh 1986; Bromily 1991; Miller and Leiblein 1996; Reuer and Lieblein 2000).

  4. Firms active in financial intermediation and insurance, portfolio companies and management activities of holdings, extra-territorial organizations, real estate firms and enterprises with only foreign activities are excluded from the dataset.

  5. A net loss does not necessarily point to real distress. It could simply result from low financial revenues from participations in other firms, or high extraordinary expenses (for example, exceptional write-offs or losses from asset sales). Tax avoidance may underlie the reporting of negative extraordinary results.

  6. This procedure is similar to “Chapter 11” in the U.S. and “administrative receivership” in the U.K. (Kaiser 1996; Couwenberg 2001). Although the basic intention of the Belgian reorganization procedure is to stimulate recovery of distressed firms, it is usually unsuccessful and strongly oriented towards bankruptcy. A similarly low popularity and success rate is found in other European countries (Couwenberg 2001).

  7. We limit our observation window to January 1st, 1990 since we lack reliable, complete and systematic annual account information for the fiscal years before 1990. This truncated observation window implies that the exit paths of the exits from 2000 are by design longer, as compared to the exits from 1998 or 1999. Sensitivity analyses controlling for this effect, however indicate that our results are insensitive to the truncated observation window.

  8. Although not appropriate in the current research setting, hazard models have been tested as a sensitivity analysis. These models lead to qualitatively similar conclusions.

  9. This results from the information and monitoring advantage of suppliers over banks (Schwartz and Whitcomb 1979).

  10. Bank monitoring may also accelerate forced liquidation of economically inefficient firms (Diamond 1984). When their debts are secured, banks are pro liquidation.

  11. Supplementary model estimations including short term financial debts as an additional control variable indicates that high short term financial debts postpone voluntary liquidation, but accelerate bankruptcy.

  12. Note that all firms in our population have survived the critical starting phase of 5 years. Older SMEs, as compared to younger SMEs are often more risk-averse, hold larger amounts of cash and are active on niche markets in mature industries, with a strong competitive position driven by technical competences.

  13. Value added and profitability can also be measured by using operational assets instead of total assets as the denominator. Sensitivity analyses for these alternative measures do not change the conclusions.

  14. Although firms may respond to distress by a adopting a growth strategy, severely declining organizations and distressed firms with internal resource constraints rather resort to organizational retrenchment and asset reductions (D’Aveni 1989; Chowdhury and Lang 1996; Robbins and Pearce 1992; Rasheed 2005).

  15. The huge difference between average and median size is driven by some very large firms in the dataset. 87.53% of the exits concern small firms and 67.13% concern micro-sized firms (i.e. total assets below 2 million € and less than 10 employees).

  16. All results of the robustness tests can be obtained upon simple request to the authors.

  17. Outlier deletion reduces the dataset to 2,272 court driven exits and 2,277 voluntary liquidations.

  18. In the Heckman-corrected model for court driven exits, the inverse Mill’s ratio (IVM) is not significant (p = 0.787). In the model for voluntary liquidations, IVM is significant (p = 0.000).

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Acknowledgements

The authors would like to thank Antoon Lenaert (National Bank of Belgium), Cécile Buydens and Guy Delvaux (National Bank of Belgium) for their helpful cooperation with Sofie Balcaen’s doctoral research and provision of the requisite data. The authors also recognize the indispensable contributions of Richard Taffler, Cynthia Van Hulle, Koen Schoors, Charles Van Wymeersch, Didier Van Caillie and Wouter De Maeseneire. Further, the suggestions of two anonymous reviewers have contributed to the development of the paper. We gratefully acknowledge the financial assistance of the Ghent University Special Research Fund, the Hercules Fund, and of the Policy Research Center in Entrepreneurship and International Business.

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Authors and Affiliations

  1. Department of Accountancy and Corporate Finance, Faculty of Economics and Business Administration, Ghent University, Kuiperskaai 55E, 9000, Ghent, Belgium

    Sofie Balcaen

  2. Department of Accountancy and Corporate Finance, Ghent University, Kuiperskaai 55E, 9000, Ghent, Belgium

    Sophie Manigart

  3. Vlerick Leuven Ghent Management School, Reep 1, 9000, Ghent, Belgium

    Sophie Manigart & Hubert Ooghe

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  1. Sofie Balcaen
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Correspondence to Sophie Manigart.

Appendix

Appendix

Table 7 Calculation of the recurring profit/loss after taxes
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Table 8 Spearman correlations between the continuous explanatory and control variables for the subsample of court driven exits (N = 2,533)
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Table 9 Spearman correlations between the continuous explanatory and control variables for the subsample of voluntary liquidations (N = 2,700)
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Table 10 Results of the tobit models for the court driven exits (N = 2,531) and the voluntary liquidations (2,644), using Huber/White robust standard errors
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Table 11 Results of the tobit models for the court driven exits (N = 2,531) and the voluntary liquidations (2,644), using net cash instead of cash
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Balcaen, S., Manigart, S. & Ooghe, H. From distress to exit: determinants of the time to exit. J Evol Econ 21, 407–446 (2011). https://doi.org/10.1007/s00191-010-0192-2

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