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Un Modelo de alerta temprana para el sistema financiero colombiano

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  • José Eduardo Gómez-González

    ()

  • Inés Paola Orozco Hinojosa

    ()

Abstract

En este trabajo se presenta un modelo estadístico de alerta temprana que utiliza modelos de duraciónpara evaluar el estado corriente y pronosticar el estado futuro de la salud financiera de los bancos enColombia. En el artículo se discuten las ventajas que tiene utilizar modelos de duración como modelosestadísticos de alerta temprana frente a los más comúnmente utilizados modelos de respuesta binaria.Se argumenta que el modelo aquí presentado, que estudia la probabilidad de deterioro de los créditosa partir la salud financiera de las contrapartes de los bancos, puede ser un buen complemento a un modelo de alerta temprana que estudie directamente la probabilidad de quiebra de las entidades financieras. La capacidad de pronóstico dentro de muestra del modelo es buena, y podría pensarse que la capacidad de pronóstico fuera de muestra también es buena, ya que la muestra de créditos comerciales utilizada en las estimaciones es bastante representativa.

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Bibliographic Info

Article provided by BANCO DE LA REPÚBLICA - ESPE in its journal ENSAYOS SOBRE POLÍTICA ECONÓMICA.

Volume (Year): (2010)
Issue (Month): ()
Pages:

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Handle: RePEc:col:000107:009428

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Related research

Keywords: modelos estadísticos de alerta temprana; modelos de duración; intensidades de transición.;

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  1. Marco Arena, 2005. "Bank Failures and Bank Fundamentals: A Comparative Analysis of Latin America and East Asia during the Nineties using Bank-Level Data," Working Papers 05-19, Bank of Canada.
  2. 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.
  3. Daley, J & Matthews, Kent & Whitfield, Keith, 2006. "Too-Big-To-Fail: Bank Failure and Banking Policy in Jamaica," Cardiff Economics Working Papers E2006/4, Cardiff University, Cardiff Business School, Economics Section.
  4. Olivier BROSSARD (LEREPS-GRES ) & Frédéric DUCROZET (PSE - Crédit Agricole) & Adrian ROCHE (EconomiX - Crédit Agricole), 2007. "An Early Warning Model for EU banks with Detection of the Adverse Selection Effect," Cahiers du GRES 2007-08, Groupement de Recherches Economiques et Sociales.
  5. Henrik Andersen, 2008. "Failure prediction of Norwegian banks: A Logit approach," Working Paper 2008/02, Norges Bank.
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