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Predicción de quiebras empresariales en economías emergentes: uso de un modelo logístico mixto || Bankruptcy Prediction in Emerging Economies: Use of a Mixed Logistic Model

Author

Listed:
  • Caro, Norma Patricia

    (Facultad de Ciencias Económicas. Universidad Nacional de Córdoba (Argentina))

  • Díaz, Margarita

    (Facultad de Ciencias Económicas. Universidad Nacional de Córdoba (Argentina))

  • Porporato, Marcela

    (School of Administrative Studies (SAS). York University, Toronto (Canadá))

Abstract

Este trabajo replica y adapta el modelo de Jones y Hensher (2004) a los datos de una economía emergente con el propósito de evaluar su validez externa. Se compara el desempeño del modelo logístico estándar en relación con el modelo logístico mixto para predecir el riesgo de crisis en el periodo 1993-2000, utilizando estados contables de empresas argentinas y ratios definidos en estudios de Altman y Jones y Hensher. Como en estudios anteriores, rentabilidad, rotación, endeudamiento y flujo de fondos operativos explican la probabilidad de crisis financiera. La contribución de esta nueva metodología reduce la tasa de error del tipo I a un 9 %. Se demuestra que el modelo logístico mixto, que tiene en cuenta la heterogeneidad no observada, supera ampliamente el desempeño del modelo logístico estándar. || This study is a replication and adaptation of Jones and Hensher (2004) model in an emerging economy with the purpose of testing its eternal validity. It compares the logistic standard model's performance with the logistic mixed model to predict bankruptcy risk of Argentinean companies between 1993-2000 by using financial statements and ratios defined in previous studies by Altman and Jones and Hensher. Similar to previous studies, profitability, asset turnover, debt and cash flow from operations explain financial distress' probability. The main contribution of this new methodology is the important reduction of error type I to the 9 %. This study asserts that the logistic mixed model, that considers the effect of non-observed heterogeneity, significantly improves the performance of the logistic standard model.

Suggested Citation

  • Caro, Norma Patricia & Díaz, Margarita & Porporato, Marcela, 2013. "Predicción de quiebras empresariales en economías emergentes: uso de un modelo logístico mixto || Bankruptcy Prediction in Emerging Economies: Use of a Mixed Logistic Model," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 16(1), pages 200-215, December.
    • Handle: RePEc:pab:rmcpee:v:16:y:2013:i:1:p:200-215
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    References listed on IDEAS

    as
    1. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
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    3. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
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    7. Altman, Edward I., 1984. "The success of business failure prediction models : An international survey," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 171-198, June.
    8. Edward I Altman & Tara K N Baidya & Luis Manoel Ribeiro Dias, 1979. "Assessing Potential Financial Problems for Firms in Brazil," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 10(2), pages 9-24, June.
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    More about this item

    Keywords

    modelo logístico mixto; estados contables; ratios financieros; crisis financiera; predicción de quiebra; Argentina; mixed logistic model; financial statements; accounting ratios; financial distress; bankruptcy prediction; Argentina;
    All these keywords.

    JEL classification:

    • M4 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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