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Un análisis de riesgo de crédito de las empresas del sector real y sus determinantes

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  • Javier Gutiérrez Rueda

    ()

Abstract

En la literatura se considera al riesgo de crédito como una de las principales fuentes de vulnerabilidad para el sistema financiero, por lo que su correcta medición resulta de vital importancia tanto para el sistema como para los agentes que hacen parte del mercado de crédito. Este documento tiene como objetivo identificar los determinantes del riesgo de crédito a través del estudio de la probabilidad de que una empresa incumpla con el pago de sus créditos. El análisis se realiza para el periodo comprendido entre 1998 y 2007. Siguiendo los hallazgos de la literatura relacionada con este tema, se emplea un modelo Probit Heteroscedástico con efectos no lineales, el cual muestra que la rentabilidad, la liquidez y el endeudamiento son los principales determinantes de este incumplimiento. Adicionalmente, se utiliza un modelo de regresión por cuantiles para identificar los efectos de los factores macroeconómicos sobre dicha probabilidad. Los resultados de este análisis indican que el impacto de estos factores varían a lo largo de la distribución de default y que estos tienen un mayor efecto sobre los deudores más riesgosos. Estos ejercicios se complementan con un análisis de sensibilidad, el cual evidencia la vulnerabilidad de los intermediarios de crédito ante cambios en el ritmo de crecimiento del la economía.

Suggested Citation

  • Javier Gutiérrez Rueda, 2010. "Un análisis de riesgo de crédito de las empresas del sector real y sus determinantes," Temas de Estabilidad Financiera 046, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:temest:046
    DOI: 10.32468/tef.46
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    File URL: https://doi.org/10.32468/tef.46
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    References listed on IDEAS

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    More about this item

    Keywords

    Riesgo de crédito; probabilidad de default; Probit Heteroscedástico; regresión por cuantiles; análisis de sensibilidad.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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