IDEAS home Printed from https://ideas.repec.org/p/bdr/temest/046.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://doi.org/10.32468/tef.46
    Download Restriction: no
    ---><---

    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. 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.
    3. 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.
    4. Cornelißen, Thomas, 2005. "Standard errors of marginal effects in the heteroskedastic probit model," Hannover Economic Papers (HEP) dp-320, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    5. Andrew Benito & Francisco Javier Delgado & Jorge Martínez Pagés, 2004. "A synthetic indicator of financial pressure for spanish firms," Working Papers 0411, Banco de España;Working Papers Homepage.
    6. 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.
    7. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    8. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    9. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    10. Oscar Martínez, 2003. "Determinantes De Fragilidad En Las Empresas Colombianas," BORRADORES DE ECONOMIA 002300, BANCO DE LA REPÚBLICA.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Javier Gutiérrez Rueda, 2010. "Un análisis de riesgo de crédito de las empresas del sector real y sus determinantes," Vniversitas Económica 008291, Universidad Javeriana - Bogotá.
    2. 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.
    3. Belaid, Faiçal & Boussaada, Rim & Belguith, Houda, 2017. "Bank-firm relationship and credit risk: An analysis on Tunisian firms," Research in International Business and Finance, Elsevier, vol. 42(C), pages 532-543.
    4. Elmas Yaldiz Hanedar & Eleonora Broccardo & Flavio Bazzana, 2012. "Collateral Requirements of SMEs:The Evidence from Less–Developed Countries," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0034, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    5. Koh, SzeKee & Durand, Robert B. & Limkriangkrai, Manapon, 2015. "The value of Saints and the price of Sin," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 56-72.
    6. Li, Ming-Yuan Leon, 2009. "Value or volume strategy?," Finance Research Letters, Elsevier, vol. 6(4), pages 210-218, December.
    7. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
    8. Aaron Jackson & William Miles, 2009. "Quantitative goals for monetary policy: a quantile regression approach," Applied Economics, Taylor & Francis Journals, vol. 41(16), pages 2065-2071.
    9. Jacob A. Bikker & Laura Spierdijk & Paul Finnie, 2006. "The Impact of Bank Size on Market Power," DNB Working Papers 120, Netherlands Central Bank, Research Department.
    10. Asongu, Simplice A. & Biekpe, Nicholas, 2018. "ICT, information asymmetry and market power in African banking industry," Research in International Business and Finance, Elsevier, vol. 44(C), pages 518-531.
    11. Robert Kelly & Eoin Brien & Rebecca Stuart, 2015. "A long-run survival analysis of corporate liquidations in Ireland," Small Business Economics, Springer, vol. 44(3), pages 671-683, March.
    12. Eduardo Acosta-González & Fernando Fernández-Rodríguez & Hicham Ganga, 2019. "Predicting Corporate Financial Failure Using Macroeconomic Variables and Accounting Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 227-257, January.
    13. Bruneau, C. & de Bandt, O. & El Amri, W., 2012. "Macroeconomic fluctuations and corporate financial fragility," Journal of Financial Stability, Elsevier, vol. 8(4), pages 219-235.
    14. Jaqueline Terra Moura Marins & Myrian Beatriz Eiras das Neves, 2013. "Credit Default and Business Cycles: an investigation of this relationship in the Brazilian corporate credit market," Working Papers Series 304, Central Bank of Brazil, Research Department.
    15. Luciana Barbosa & Paulo Soares de Pinho, 2017. "Operational cycle and tax liabilities as determinants of corporate credit risk," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    16. Zhang, Jian & Mishra, Ashok K. & Hirsch, Stefan & Li, Xiaoshun, 2020. "Factors affecting farmland rental in rural China: Evidence of capitalization of grain subsidy payments," Land Use Policy, Elsevier, vol. 90(C).
    17. Leon Li & Nen-Chen Richard Hwang, 2017. "Prospect Theory and Earnings Manipulation: Examination of the Non-Uniform Relationship between Earnings Manipulation and Stock Returns Using Quantile Regression," Working Papers in Economics 17/25, University of Waikato.
    18. Daniel Pollmann & Thomas Dohmen & Franz Palm, 2020. "Robust Estimation of Wage Dispersion with Censored Data: An Application to Occupational Earnings Risk and Risk Attitudes," De Economist, Springer, vol. 168(4), pages 519-540, December.
    19. Gabriel Jiménez & Steven Ongena & José‐Luis Peydró & Jesús Saurina, 2014. "Hazardous Times for Monetary Policy: What Do Twenty‐Three Million Bank Loans Say About the Effects of Monetary Policy on Credit Risk‐Taking?," Econometrica, Econometric Society, vol. 82(2), pages 463-505, March.
    20. Kaza, Nikhil, 2010. "Understanding the spectrum of residential energy consumption: A quantile regression approach," Energy Policy, Elsevier, vol. 38(11), pages 6574-6585, November.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bdr:temest:046. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Clorith Angélica Bahos-Olivera). General contact details of provider: https://edirc.repec.org/data/brcgvco.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.