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Federal Reserve Bank of Atlanta
FRB Atlanta Working Paper
Forecasting using relative entropy
John C. Robertson
Ellis W. Tallman
Charles H. Whiteman

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.

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John C. Robertson & Ellis W. Tallman & Charles H. Whiteman, Forecasting using relative entropy, Federal Reserve Bank of Atlanta, FRB Atlanta Working Paper 2002-22, 2002.
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Keywords: Forecasting
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