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The paper explores the justification for, and application of, Bayesian priors in forecasting a vector autoregression. A nonsymmetric, random‐walk prior outperforms three alternative time‐series representations in forecasting five series of the U.S. hog market.
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Bessler et al. (1986) studied this question.
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