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Forecasting Using Relative Entropy
2003
Social Science Research Network
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.
doi:10.2139/ssrn.355460
fatcat:yqnzjmupnfdb7euigt2r2t4gai