Posted

May 12, 2012 08:20:03 AM

Date

2012-04

Author

Luis Fernando Melo and Rubén Albeiro Loaiza Maya

Affiliation

Bank of the Republic of Colombia

Title

Bayesian Forecast Combination for Inflation Using Rolling Windows: An Emerging Country Case

Summary /
Abstract

Typically, when forecasting inflation rates, there are a variety of individual models and a combination of several of these models. We implement a Bayesian shrinkage combination methodology to include information that is not captured by the individual models using expert forecasts as prior information. To take into account two common characteristics in emerging countries’ economies, possible parameter instabilities and non-stationary dynamics, we use a rolling estimation windows technique for series integrated of order one. The empirical results of Colombian inflation show that the Bayesian forecast combination model outperforms the individual models and the random walk predictions for every evaluated forecast horizon. Moreover, these results outperform shrinkage forecasts that consider other priors as equal or zero weights.

Keywords

Forecast combination, shrinkage, expert forecasts, rolling window estimation, inflation forecasts.

URL

http://d.repec.org/n?u=RePEc:col:000094:009511&r=cba

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