Forecasting using relative entropy

John Robertson, Ellis Tallman and Charles Whiteman ()

No 2002-22, FRB Atlanta Working Paper from Federal Reserve Bank of Atlanta

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: Forecasting (search for similar items in EconPapers)
Date: 2002
New Economics Papers: this item is included in nep-ets and nep-rmg
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Citations: View citations in EconPapers (14)

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Journal Article: Forecasting Using Relative Entropy (2005)
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