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Determinantes De Fragilidad En Las Empresas Colombianas

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  • Oscar Martínez

Abstract

Una de las mayores amenazas para toda empresa es caer en un estado de insolvencia. Este tipo de amenaza a la estabilidad financiera de las empresas es relevante no solo para inversionistas y empleados, sino también para prestamistas del sector financiero, auditores y autoridades reguladoras entre otros. Usando técnicas de regresión probit este estudio desarrolla un modelo en que se identifican las variables relevantes para pronosticar el estrés o fragilidad financiera de las empresas en Colombia en el año 2001. A partir de los estados financieros que 9000 empresas reportaron en el año 2000, el modelo identificó correctamente al 82% de las empresas frágiles y no frágiles. Los resultados confirman la importancia de los indicadores de rentabilidad, endeudamiento y liquidez en la solvencia presentada por las empresas, puntualmente la utilidad antes de impuestos sobre activo, obligaciones financieras sobre activo y disponible sobre activo respectivamente.

Suggested Citation

  • Oscar Martínez, 2003. "Determinantes De Fragilidad En Las Empresas Colombianas," Borradores de Economia 2300, Banco de la Republica.
    • Handle: RePEc:col:000094:002300
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    1. Leonardo Villar G. & Hernán Rincón C., 2001. "Flujos de capital y regímenes cambiarios en la década de los 90," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 19(39), pages 5-71, June.
    2. Platt, Harlan D. & Platt, Marjorie B., 1991. "A note on the use of industry-relative ratios in bankruptcy prediction," Journal of Banking & Finance, Elsevier, vol. 15(6), pages 1183-1194, December.
    3. Harris, Milton & Raviv, Artur, 1991. "The Theory of Capital Structure," Journal of Finance, American Finance Association, vol. 46(1), pages 297-355, March.
    4. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    5. Sunti Tirapat & Aekkachai Nittayagasetwat, 1999. "An Investigation of Thai Listed Firms' Financial Distress Using Macro and Micro Variables," Multinational Finance Journal, Multinational Finance Journal, vol. 3(2), pages 103-125, June.
    6. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    7. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
    8. Lo, Andrew W., 1986. "Logit versus discriminant analysis : A specification test and application to corporate bankruptcies," Journal of Econometrics, Elsevier, vol. 31(2), pages 151-178, March.
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    Cited by:

    1. Angela González Arbeláez, 2010. "Determinantes del riesgo de crédito comercial en Colombia," Temas de Estabilidad Financiera 045, Banco de la Republica de Colombia.
    2. Nancy Eugenia Zamudio Gómez, 2007. "Determinantes de la Probabilidad de Incumplimiento de las Empresas Colombianas," Borradores de Economia 466, Banco de la Republica de Colombia.
    3. Javier Gutiérrez Rueda, 2010. "Un análisis de riesgo de crédito de las empresas del sector real y sus determinantes," Vniversitas Económica 8291, Universidad Javeriana - Bogotá.

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    Keywords

    Fragilidad financiera;

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