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Firm Failure Prediction Models: A Critique and a Review of Recent Developments

In: Advances in Entrepreneurial Finance

Author

Listed:
  • Richard L. Constand

    (California State University)

  • Rassoul Yazdipour

Abstract

This chapter first argues that the literature on financial distress and failure prediction has totally ignored the cause of failure – managers and owner-managers as decision makers – and instead has almost exclusively focused on the effect of failure, the financial data. The chapter then provides a review of the current state of the failure prediction literature. Recent studies that focus on small and medium-sized enterprises (SMEs) are covered next. We arrive at the same conclusion that after 35 years of academic inquiry into bankruptcy prediction, and despite all the sophisticated models and methodologies used in studies of the effects of firm failure, there is “no academic consensus as to the most useful method for ­predicting corporate bankruptcy.” At the end, the chapter discusses how psychological ­phenomena and principles, also known as heuristics or mental shortcuts, might be utilized in building more powerful success/failure prediction models.

Suggested Citation

  • Richard L. Constand & Rassoul Yazdipour, 2011. "Firm Failure Prediction Models: A Critique and a Review of Recent Developments," Springer Books, in: Advances in Entrepreneurial Finance, chapter 0, pages 185-204, Springer.
  • Handle: RePEc:spr:sprchp:978-1-4419-7527-0_10
    DOI: 10.1007/978-1-4419-7527-0_10
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    Cited by:

    1. Salima Smiti & Makram Soui, 2020. "Bankruptcy Prediction Using Deep Learning Approach Based on Borderline SMOTE," Information Systems Frontiers, Springer, vol. 22(5), pages 1067-1083, October.
    2. Fejér-Király Gergely, 2015. "Bankruptcy Prediction: A Survey on Evolution, Critiques, and Solutions," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 3(1), pages 93-108, December.

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