Forecasting Using Relative Entropy
FRB of Atlanta Working Paper No. 2002-22
33 Pages Posted: 10 Jan 2003
Date Written: November 2002
Abstract
The paper describes a relative entropy procedure for imposing moment restrictions on simulated forecast distributions from a variety of models. Starting from an empirical forecast distribution for some variables of interest, the technique generates a new empirical distribution that satisfies a set of moment restrictions. The new distribution is chosen to be as close as possible to the original in the sense of minimizing the associated Kullback-Leibler Information Criterion, or relative entropy. The authors illustrate the technique by using several examples that show how restrictions from other forecasts and from economic theory may be introduced into a model's forecasts.
Keywords: approximate prior information, Kullback-Leibler Information Criterion, relative numerical efficiency
JEL Classification: E44, C53
Suggested Citation: Suggested Citation
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