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More than a Dummy: The Probability of Failure, Survival and Acquisition of Private Firms in Financial Distress

Author

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  • Thomas B. Astebro

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • J. K. Winter

Abstract

We discuss three methodological issues concerning forecasts of the outcome of financial distress. First, we argue that rather than using a binary model the outcome of financial distress should be modeled using a multinomial specification that distinguishes between failure, survival as going concern, and acquisition. We also argue for a random rather than matched-pair sampling technique to better reflect decision making reality. Finally, we investigate the value of using industry-mean adjusted regressors. We find that the binary bankruptcy model is mis-specified relative to the multinomial model, that the matched sampling technique overstates model accuracy and that industry specific intercepts have better explanatory power than industry-adjusted regressors.

Suggested Citation

  • Thomas B. Astebro & J. K. Winter, 2012. "More than a Dummy: The Probability of Failure, Survival and Acquisition of Private Firms in Financial Distress," Post-Print hal-00715485, HAL.
    • Handle: RePEc:hal:journl:hal-00715485
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    Citations

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    Cited by:

    1. XU Peng, 2021. "Population Aging and Small Business Exits," Discussion papers 21091, Research Institute of Economy, Trade and Industry (RIETI).
    2. Iwasaki, Ichiro & Kočenda, Evžen & Shida, Yoshisada, 2021. "Distressed acquisitions: Evidence from European emerging markets," Journal of Comparative Economics, Elsevier, vol. 49(4), pages 962-990.
    3. Carmen Cotei & Joseph Farhat, 2018. "The M&A exit outcomes of new, young firms," Small Business Economics, Springer, vol. 50(3), pages 545-567, March.
    4. Carmen Cotei & Joseph Farhat & Indu Khurana, 2022. "The impact of policy uncertainty on the M&A exit of startup firms," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(1), pages 99-120, January.
    5. Kaiser, Ulrich & Kuhn, Johan M., 2020. "The value of publicly available, textual and non-textual information for startup performance prediction," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
    6. Stéphane Esquerré, 2019. "How do judges judge? Evidence of local effect on French bankruptcy judgments," Working Papers hal-02291688, HAL.
    7. Manuel Rico & Naresh R. Pandit & Francisco Puig, 2021. "SME insolvency, bankruptcy, and survival: an examination of retrenchment strategies," Small Business Economics, Springer, vol. 57(1), pages 111-126, June.
    8. Nina Ponikvar & Katja Zajc Kejžar & Darja Peljhan, 2018. "The role of financial constraints for alternative firm exit modes," Small Business Economics, Springer, vol. 51(1), pages 85-103, June.
    9. Kaiser, Ulrich & Kuhn, Johan Moritz, 2020. "Value of Publicly Available, Textual and Non-textuThe al Information for Startup Performance Prediction," IZA Discussion Papers 13029, Institute of Labor Economics (IZA).
    10. Salwa Kessioui & Michalis Doumpos & Constantin Zopounidis, 2023. "A Bibliometric Overview of the State-of-the-Art in Bankruptcy Prediction Methods and Applications," World Scientific Book Chapters, in: Emilios Galariotis & Alexandros Garefalakis & Christos Lemonakis & Marios Menexiadis & Constantin Zo (ed.), Governance and Financial Performance Current Trends and Perspectives, chapter 6, pages 123-153, World Scientific Publishing Co. Pte. Ltd..

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