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Combinación de pronósticos de la inflación en presencia de cambios estructurales

Author

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  • Luis Fernando Melo Velandia
  • Héctor M. Núñez Amortegui

Abstract

En este trabajo se implementan diferentes metodologías de combinación de pronósticos para la inflación colombiana durante el período trimestral comprendido entre 1999:I y 2003:I I. Los métodos de combinación propuestos permiten modelar cambios estructurales con el objeto de capturar el cambio de nivel de la inflación ocurrido en 1998 y 1999. Los resultados obtenidos muestran que la metodología de Castaño y Melo (1998), que no considera cambios estructurales, sigue siendo apropiada para pronósticos de horizontes de 1, 2 y 3 trimestres. Sin embargo, para horizontes mayores las metodologías de combinación que consideran cambios estructurales son las mejores, en el sentido de que tienen el menor error cuadrático medio de predicción.

Suggested Citation

  • Luis Fernando Melo Velandia & Héctor M. Núñez Amortegui, 2004. "Combinación de pronósticos de la inflación en presencia de cambios estructurales," Borradores de Economia 2153, Banco de la Republica.
    • Handle: RePEc:col:000094:002153
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    Cited by:

    1. Luis Fernando Melo & Rubén Albeiro Loaiza Maya, 2012. "Bayesian Forecast Combination for Inflation Using Rolling Windows: An Emerging Country Case," Borradores de Economia 705, Banco de la Republica de Colombia.
    2. Eliana González, 2010. "Bayesian Model Averaging. An Application to Forecast Inflation in Colombia," Borradores de Economia 7013, Banco de la Republica.
    3. Gomez, Miguel I. & Gonzalez, Eliana & Melo, Luis F. & Torres, Jose L., 2006. "Forecasting Food Price Inflation, Challenges for Central Banks in Developing Countries using an Inflation Targeting Framework: the Case of Colombia," 2006 Annual meeting, July 23-26, Long Beach, CA 21181, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Melo, Luis F. & Loaiza, Rubén A. & Villamizar-Villegas, Mauricio, 2016. "Bayesian combination for inflation forecasts: The effects of a prior based on central banks’ estimates," Economic Systems, Elsevier, vol. 40(3), pages 387-397.
    5. Eliana Gómez & Miguel I. Gómez & Luis F.Melo & José Luis Torres, 2006. "Forecasting Food Price Inflation in Developing Countries with Inflation Targeting Regimes: the Colombian Case," Borradores de Economia 409, Banco de la Republica de Colombia.
    6. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: el caso colombiano," Coyuntura Económica, Fedesarrollo, December.
    7. Luis Eduardo Arango & Luz Adriana Flórez, 2004. "Expectativas de actividad económica en Colombia y estructura a plazo: un poco más de evidencia," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 22(47), pages 126-160, December.
    8. Eliana González, 2011. "Forecasting With Many Predictors. An Empirical Comparison," Borradores de Economia 643, Banco de la Republica de Colombia.
    9. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: El caso colombiano," Borradores de Economia 11252, Banco de la Republica.

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