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Surviving Chapter 11 Bankruptcies: Duration and Payoff?

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  • Brad Wong
  • Graham Partington
  • Maxwell Stevenson
  • Violet Torbey

Abstract

Three of the authors previously developed a model to predict the duration of Chapter 11 bankruptcy and the payoff to shareholders (Partington et al., 2001). This work augments that study using a much larger sample to re‐estimate the model and assess its stability. It also provides an opportunity for out‐of‐sample testing of predictive accuracy. The resulting models are based on Cox's proportional hazards model and the current article points to the need to test two important assumptions underlying the model. First, that the hazards are proportional and, second, that censoring is independent of the event studied. Using the extended data set, all the previously significant accounting variables drop out of the model and only two covariates of the original model remain significant. These are the market wide credit spread and the market capitalization of the firm, both measured immediately prior to the firm's entry to Chapter 11. Receiver operating characteristic curves are then used to assess the predictive accuracy of the original and extended models. The results show that Lachenbruch tests can provide a misleading indication of predictive ability out of sample. Using the Lachenbruch method of in‐sample testing, both models show predictive power, but in a true out‐of‐sample test they fail dismally. The lessons of this work are relevant to better predicting the gains and losses likely to accrue to shareholders of companies in Chapter 11 bankruptcy and in similar administrative arrangements in other jurisdictions.

Suggested Citation

  • Brad Wong & Graham Partington & Maxwell Stevenson & Violet Torbey, 2007. "Surviving Chapter 11 Bankruptcies: Duration and Payoff?," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 363-387, September.
  • Handle: RePEc:bla:abacus:v:43:y:2007:i:3:p:363-387
    DOI: 10.1111/j.1467-6281.2007.00236.x
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    Citations

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    Cited by:

    1. Maria H. Kim & Graham Partington, 2015. "Dynamic forecasts of financial distress of Australian firms," Australian Journal of Management, Australian School of Business, vol. 40(1), pages 135-160, February.
    2. Betz, Jennifer & Krüger, Steffen & Kellner, Ralf & Rösch, Daniel, 2020. "Macroeconomic effects and frailties in the resolution of non-performing loans," Journal of Banking & Finance, Elsevier, vol. 112(C).
    3. Betz, Jennifer & Kellner, Ralf & Rösch, Daniel, 2016. "What drives the time to resolution of defaulted bank loans?," Finance Research Letters, Elsevier, vol. 18(C), pages 7-31.
    4. Antill, Samuel & Grenadier, Steven R., 2019. "Optimal capital structure and bankruptcy choice: Dynamic bargaining versus liquidation," Journal of Financial Economics, Elsevier, vol. 133(1), pages 198-224.
    5. James Routledge & David Morrison, 2012. "Insolvency administration as a strategic response to financial distress," Australian Journal of Management, Australian School of Business, vol. 37(3), pages 441-459, December.
    6. 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..
    7. Jennifer Betz & Ralf Kellner & Daniel Rösch, 2021. "Time matters: How default resolution times impact final loss rates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 619-644, June.
    8. Maria Heui-Yeong Kim & Shiguang Ma & Yanran Annie Zhou, 2016. "Survival prediction of distressed firms: evidence from the Chinese special treatment firms," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 21(3), pages 418-443, July.
    9. Goodwin, John & Routledge, James, 2021. "Determinants of the duration of the voluntary administration process: An unconditional quantile regression analysis," Journal of Contemporary Accounting and Economics, Elsevier, vol. 17(3).

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