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Relación entre el riesgo sistémico del sistema financiero y el sector real

Author

Listed:
  • Wilmar Cabrera

  • Javier Gutiérrez Rueda

  • Juan Carlos Mendoza

  • Luis Fernando Melo

Abstract

En este documento se analiza la relación existente entre el riesgo del sector real y del sistema financiero. Para esto, se estima un modelo FAVAR en el cual se incluyen un conjunto de variables que reflejan la evolución de la dinámica común de las series de los diferentes sectores de la economía y un componente idiosincrático. Dado el proceso generador de datos identificado en el modelo antes mencionado, es posible estimar las medidas de riesgo del sistema financiero y del sector real utilizando la metodología de regresión por cuantiles. Posteriormente, se usa la medida de CoV aR, propuesta por Adrian & Brunnermeier (2011) para medir el grado de codependencia entre los riesgos de estos sectores. Los resultados muestran que los indicadores de riesgo reflejan las situaciones de estrés que se han presentado en el sector real y el financiero de la economía colombiana. Adicionalmente, mediante las estimaciones del modelo FAVAR se realiza un análisis de impulso respuesta para analizar cómo se trasmiten choques adversos entre un sector y otro.

Suggested Citation

  • Wilmar Cabrera & Javier Gutiérrez Rueda & Juan Carlos Mendoza & Luis Fernando Melo, 2011. "Relación entre el riesgo sistémico del sistema financiero y el sector real," Temas de Estabilidad Financiera 062, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:temest:062
    DOI: 10.32468/tef.62
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    References listed on IDEAS

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    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. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    3. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    4. Miguel Morales & Dairo Estrada, 2010. "A financial stability index for Colombia," Annals of Finance, Springer, vol. 6(4), pages 555-581, October.
    5. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G2 - Financial Economics - - Financial Institutions and Services
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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