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Métodos De Combinación De Pronósticos:Una Aplicación A La Inflación Colombiana

  • Elkin Castaño V.


  • Luis Fernando Melo Velandia


En este trabajo se presentan algunos métodos de combinación de pronósticos de diferentes modelos econométricos. Estas metodologías tienen como principal objetivo encontrar una combinación lineal de pronósticos de diferentes modelos que produzca una predicción mejorada en términos de precisión. Basados en estas técnicas se realizan dos ejercicios: en la primera aplicación se emplean estos métodos sobre quince modelos trimestrales de la inflación colombiana para pronósticos en el periodo comprendido entre 1992:I y 1998 :II considerando horizontes desde uno hasta cuatro trimestres. Los resultados de este análisis muestran una mejoría significativa en las predicciones; en efecto, el pronóstico combinado comparado con los pronósticos del mejor de los modelos econométricos reporta ganancias en precisión (RMSE); en caso del horizonte de un trimestre es del 16.1%; para el horizonte de dos trimestres es del 42%; para el horizonte tres del 21.3% y del 12.8% para el horizonte de cuatro trimestres. La segunda aplicación de las metodologías de combinación de pronósticos se realiza utilizando un ejercicio de simulación, el cual se basa en modelos similares a los empleados en el primer ejercicio; los resultados obtenidos muestran que bajo técnicas adecuadas de combinación de pronósticos es posible obtener alrededor de un 50% y 35% de ganancia en precisión con respecto a los modelos individuales para horizontes de uno y cuatro trimestres, respectivamente.

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Paper provided by BANCO DE LA REPÚBLICA in its series BORRADORES DE ECONOMIA with number 003212.

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Length: 58
Date of creation: 30 Nov 1998
Date of revision:
Handle: RePEc:col:000094:003212
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  5. Francis X. Diebold & Peter Pauly, 1986. "Structural change and the combination of forecasts," Special Studies Papers 201, Board of Governors of the Federal Reserve System (U.S.).
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  15. Min, C.K. & Zellner, A., 1992. ""Bayesian and Non-Bayesian Methods for Combining Models and Forecasts with Applications to Forecasting International Growth Rates"," Papers 90-92-23, California Irvine - School of Social Sciences.
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  19. Robert E. Cumby & John Huizinga, 1990. "Testing The Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions," NBER Technical Working Papers 0092, National Bureau of Economic Research, Inc.
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