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The Generalizability of Financial Distress Prediction Models: Evidence from Turkey

Author

Listed:
  • Ibrahim Onur Oz

    (Central Connecticut State University, United States)

  • Tezer Yelkenci

    (Izmir University of Economics, Turkey)

Abstract

This study analyzes five of the well-known and most cited distress prediction models in the literature. The models are implemented to continuous publicly listed industrial firms in Turkey through their original and re-estimated coefficients in a comparative way to examine their generalizability in different time periods and samples. The effect of 2008 financial crisis is also assessed to conduct a fuller analysis of the models’ prediction accuracies. The results emphasize that Ohlson (1980), Taffler (1983), Zmijewski (1984), and Shumway (2001) provide highly accurate distress classification results through their original coefficients for Turkish industrial market. On the other hand, the re-estimation of the models (other than Ohlson’s [1980]) fails to improve the prediction accuracies which are also found insignificant by considering the pre and post crisis periods.

Suggested Citation

  • Ibrahim Onur Oz & Tezer Yelkenci, 2015. "The Generalizability of Financial Distress Prediction Models: Evidence from Turkey," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 14(4), pages 685-703, December.
    • Handle: RePEc:ami:journl:v:14:y:2015:i:4:p:685-703
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    Citations

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    Cited by:

    1. Oz, Ibrahim Onur & Simga-Mugan, Can, 2018. "Bankruptcy prediction models' generalizability: Evidence from emerging market economies," Advances in accounting, Elsevier, vol. 41(C), pages 114-125.
    2. Oz, Ibrahim Onur & Yelkenci, Tezer & Meral, Gorkem, 2021. "The role of earnings components and machine learning on the revelation of deteriorating firm performance," International Review of Financial Analysis, Elsevier, vol. 77(C).

    More about this item

    Keywords

    Financial distress prediction; emerging markets; model comparison; financial crisis; multiple discriminant analysis; logit; probit; hazard model; financial ratios;
    All these keywords.

    JEL classification:

    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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