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La muestra de empresas en los modelos de predicción del fracaso: influencia en los resultados de clasificación || The Sample of Firms in Business Failure Prediction Models: Influence on Classification Results

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  • García-Gallego, Ana

    ()
    (Departamento de Economía y Estadística, Universidad de León (España))

  • Mures-Quintana, María-Jesús

    ()
    (Departamento de Economía y Estadística, Universidad de León (España))

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    Abstract

    El objetivo de este artículo es la obtención de sendos modelos de predicción del fracaso empresarial en una muestra emparejada y otra aleatoria de pequeñas y medianas empresas con domicilio en Castilla y León (España), a fin de determinar si el poder predictivo de los modelos elaborados está afectado por el método utilizado para seleccionar la muestra objeto de cada estudio. Para ello, consideramos como variables independientes un conjunto de ratios financieros, que reducimos a partir de la aplicación previa de un análisis de componentes principales. Mediante regresión logística, identificamos los factores que mejor predicen el fracaso en ambas muestras, observándose diferencias no solo en las variables significativas, sino también en los resultados de clasificación, lo que conforma la influencia del método de muestreo en los modelos. || This paper focuses on the development of both failure prediction models on a paired sample and a random sample of small and medium-sized firms with head offices located in the region of Castilla y León (Spain), in order to prove if the predictive power of the developed models is affected by the method used to derive the sample aim of each study. To estimate both models, we consider a set of financial ratios as independent variables in each one, which is first reduced by the application of a principal components analysis. Next, a logistic regression analysis is applied to identify those variables that best explain and predict failure in the two samples, where differences in the significant variables and the classification results are observed, which confirms the influence of the sampling method on the business failure prediction results.

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    Bibliographic Info

    Article provided by Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration in its journal Revista de Métodos Cuantitativos para la Economía y la Empresa.

    Volume (Year): 15 (2013)
    Issue (Month): 1 (June)
    Pages: 133-150

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    Handle: RePEc:pab:rmcpee:v:15:y:2013:i:1:p:133-150

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    Related research

    Keywords: fracaso empresarial; ratios financieros; muestreo; regression logística; predicción; business failure; financial ratios; sampling; logistic regression; prediction;

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    References

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    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, 09.
    2. S. Balcaen & H. Ooghe, 2004. "35 years of studies on business failure: an overview of the classical statistical methodologiesand their related problems," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/248, Ghent University, Faculty of Economics and Business Administration.
    3. Palepu, Krishna G., 1986. "Predicting takeover targets : A methodological and empirical analysis," Journal of Accounting and Economics, Elsevier, vol. 8(1), pages 3-35, March.
    4. Molinero, C Mar & Ezzamel, M, 1991. "Multidimensional scaling applied to corporate failure," Omega, Elsevier, vol. 19(4), pages 259-274.
    5. Antonio Trujillo-Ponce & Reyes Samaniego-Medina & Clara Cardone-Riportella, 2012. "Examining what best explains corporate credit risk: accounting-based versus market-based models," Working Papers 12.03, Universidad Pablo de Olavide, Department of Financial Economics and Accounting (former Department of Business Administration).
    6. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    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. Andreas Charitou & Evi Neophytou & Chris Charalambous, 2004. "Predicting corporate failure: empirical evidence for the UK," European Accounting Review, Taylor & Francis Journals, vol. 13(3), pages 465-497.
    9. Scott, James, 1981. "The probability of bankruptcy: A comparison of empirical predictions and theoretical models," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 317-344, September.
    10. Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
    11. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    12. Peel, MJ & Peel, DA & Pope, PF, 1986. "Predicting corporate failure-- Some results for the UK corporate sector," Omega, Elsevier, vol. 14(1), pages 5-12.
    13. Edmister, Robert O., 1972. "An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(02), pages 1477-1493, March.
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