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Factors Affecting the Probability of Bankruptcy: A Managerial Decision Based Approach

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  • Maurice Peat

Abstract

The majority of classification models developed have used a pool of financial ratios combined with statistical variable selection techniques to maximize the accuracy of the classifier constructed. Rather than follow this approach, this article seeks to provide an explicit economic basis for the selection of variables for inclusion in bankruptcy models. This search to develop an economic theory of bankruptcy augments the existing bankruptcy prediction literature. Variables which occur in bankruptcy probability expressions derived from the solution of a stochastic optimizing model of firm behaviour are ‘proxied’ by variables constructed from financial statement data. The random nature of the lifetime of a single firm provides the rationale for the use of duration or hazard‐based statistical methods in the validation of the derived bankruptcy probability expressions. Results of the validation exercise confirm that the majority of variables included in the empirical hazard formulation behave in a way that is consistent with the model of the firm. The results highlight the need for developments in the measurement of earnings dispersion.

Suggested Citation

  • Maurice Peat, 2007. "Factors Affecting the Probability of Bankruptcy: A Managerial Decision Based Approach," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 303-324, September.
  • Handle: RePEc:bla:abacus:v:43:y:2007:i:3:p:303-324
    DOI: 10.1111/j.1467-6281.2007.00232.x
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    Cited by:

    1. Elizabeth Carson & Neil Fargher & Yuyu Zhang, 2016. "Trends in Auditor Reporting in Australia: A Synthesis and Opportunities for Research," Australian Accounting Review, CPA Australia, vol. 26(3), pages 226-242, September.
    2. Alessandra Amendola & Francesco Giordano & Maria Lucia Parrella & Marialuisa Restaino, 2017. "Variable selection in high‐dimensional regression: a nonparametric procedure for business failure prediction," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(4), pages 355-368, August.
    3. Alnoor Bhimani & Mohamed Azzim Gulamhussen & Samuel Rocha Lopes, 2014. "Owner liability and financial reporting information as predictors of firm default in bank loans," Review of Accounting Studies, Springer, vol. 19(2), pages 769-804, June.
    4. 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.
    5. Elsayed, Mohamed & Elshandidy, Tamer, 2020. "Do narrative-related disclosures predict corporate failure? Evidence from UK non-financial publicly quoted firms," International Review of Financial Analysis, Elsevier, vol. 71(C).
    6. Alessandro Zeli, 2014. "The financial distress indicators trend in Italy: an analysis of medium-size enterprises," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 4(2), pages 199-221, December.
    7. David Johnstone, 2007. "Discussion of Altman and Sabato," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 358-362, September.
    8. Antonio Blanco-Oliver & Ana Irimia-Dieguez & María Oliver-Alfonso & Nicholas Wilson, 2015. "Systemic Sovereign Risk and Asset Prices: Evidence from the CDS Market, Stressed European Economies and Nonlinear Causality Tests," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(2), pages 144-166, April.
    9. Li, Shengfeng & Han, Liang & Mi, Biao, 2024. "The effects of banking market structure on corporate cash holdings and the value of cash," Journal of Empirical Finance, Elsevier, vol. 75(C).
    10. Kenth Skogsvik, 2007. "Discussion of Peat," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 325-331, September.
    11. 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.
    12. 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..
    13. Ana Paula Matias Gama & Helena Susana Amaral Geraldes, 2012. "Credit risk assessment and the impact of the New Basel Capital Accord on small and medium‐sized enterprises," Management Research Review, Emerald Group Publishing Limited, vol. 35(8), pages 727-749, July.
    14. Sumon Bhaumik & Pranab Kumar Das & Subal C. Kumbhakar, 2011. "Firm Investment & Credit Constraints in India, 1997 ??? 2006: A stochastic frontier approach," William Davidson Institute Working Papers Series wp1010, William Davidson Institute at the University of Michigan.
    15. Bhimani, Alnoor & Gulamhussen, Mohamed Azzim & Lopes, Samuel Da-Rocha, 2010. "Accounting and non-accounting determinants of default: An analysis of privately-held firms," Journal of Accounting and Public Policy, Elsevier, vol. 29(6), pages 517-532, November.
    16. Carlos Serrano-Cinca & Yolanda Fuertes-Call鮠 & Bego uti鲲ez-Nieto & Beatriz Cuellar-Fernᮤez, 2014. "Path modelling to bankruptcy: causes and symptoms of the banking crisis," Applied Economics, Taylor & Francis Journals, vol. 46(31), pages 3798-3811, November.
    17. Sailesh Tanna & Ibrahim Yousef & Matthias Nnadi, 2020. "Probability of mergers and acquisitions deal failure," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 13(1), pages 1-30, May.

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