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

Author

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  • Javier Gutiérrez Rueda

Abstract

En la literatura se considera el 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, estudiando la probabilidad de que una empresa incumpla con el pago de sus créditos. El análisis se realiza para el período 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 efectosde los factores macroeconómicos sobre dicha probabilidad. Los resultados de este análisis indican que el impacto de estos factores varía a lo largo de la distribución de default y que estos tienen un mayor efecto en 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," Vniversitas Económica, Universidad Javeriana - Bogotá, vol. 0(0), pages 1-40, March.
    • Handle: RePEc:col:000416:008291
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    File URL: http://cea.javeriana.edu.co/documents/153049/2786252/Vol.10_4_2010.pdf/1dd48d8f-c994-412a-a783-d67d81de212d
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    References listed on IDEAS

    as
    1. Glenn Hoggarth & Steffen Sorensen & Lea Zicchino, 2005. "Stress tests of UK banks using a VAR approach," Bank of England working papers 282, Bank of England.
    2. Cornelißen, Thomas, 2005. "Standard errors of marginal effects in the heteroskedastic probit model," Hannover Economic Papers (HEP) dp-320, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    4. Lennox, Clive, 1999. "Identifying failing companies: a re-evaluation of the logit, probit and DA approaches," Journal of Economics and Business, Elsevier, vol. 51(4), pages 347-364, July.
    5. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    6. Philip Bunn & Victoria Redwood, 2003. "Company accounts based modelling of business failures and the implications for financial stability," Bank of England working papers 210, Bank of England.
    7. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    8. Jimenez, Gabriel & Saurina, Jesus, 2004. "Collateral, type of lender and relationship banking as determinants of credit risk," Journal of Banking & Finance, Elsevier, vol. 28(9), pages 2191-2212, September.
    9. Bonfim, Diana, 2009. "Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 281-299, February.
    10. M. Tudela & G. Young, 2005. "A Merton-Model Approach To Assessing The Default Risk Of Uk Public Companies," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(06), pages 737-761.
    11. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    12. Oscar Martínez A., 2003. "Determinantes de fragilidad en las empresas colombianas," Temas de Estabilidad Financiera 001, Banco de la Republica de Colombia.
    13. Jim Wong & Ka-Fai Choi & Tom Pak-Wing Fong, 2008. "A Framework for Stress Testing Banks’ Credit Risk," Palgrave Macmillan Studies in Banking and Financial Institutions, in: Hans Genberg & Cho-Hoi Hui (ed.), The Banking Sector in Hong Kong, chapter 11, pages 240-260, Palgrave Macmillan.
    14. Nancy Eugenia Zamudio Gómez, 2007. "Determinantes de la Probabilidad de Incumplimiento de las Empresas Colombianas," Borradores de Economia 4292, Banco de la Republica.
    15. Javier Gutiérrez Rueda & Diego M. Vásquez E., 2008. "Un Análisis de Cointegración para el Riesgo de Crédito," Temas de Estabilidad Financiera 035, Banco de la Republica de Colombia.
    16. Jimenez, Gabriel & Salas, Vicente & Saurina, Jesus, 2006. "Determinants of collateral," Journal of Financial Economics, Elsevier, vol. 81(2), pages 255-281, August.
    17. 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.
    18. Andrew Benito & Francisco Javier Delgado & Jorge Martínez Pagés, 2004. "A synthetic indicator of financial pressure for spanish firms," Working Papers 0411, Banco de España.
    19. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, September.
    20. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    21. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    22. Oscar Martínez, 2003. "Determinantes De Fragilidad En Las Empresas Colombianas," Borradores de Economia 2300, Banco de la Republica.
    23. Arnab Bhattacharjee & Chris Higson & Sean Holly & Paul Kattuman, 2007. "Macroeconomic Conditions and Business Exit: Determinants of Failures and Acquisitions of UK Firms," CDMA Working Paper Series 200713, Centre for Dynamic Macroeconomic Analysis.
    24. Oscar Martínez A., 2003. "Determinantes de Fragilidad en las Empresas Colombianas," Borradores de Economia 259, Banco de la Republica de Colombia.
    25. Pagan, Adrian & Vella, Frank, 1989. "Diagnostic Tests for Models Based on Individual Data: A Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages 29-59, Supplemen.
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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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