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Abstract

We develop and evaluate quarterly out-of-sample individual and composite density forecasts for U.S. hog prices using data from 1975.I to 2010.IV. Individual forecasts are generated from time series models and the implied distribution of USDA outlook forecasts. Composite density forecasts are constructed using linear and logarithmic combinations, and several straightforward weighting schemes. Density forecasts are evaluated on goodness of fit (calibration) and predictive accuracy (sharpness). Logarithmic combinations using equal and mean square error weights outperform all individual density forecasts and all linear combinations. Comparison of the USDA outlook forecasts to the best logarithmic composite demonstrates the consistent superiority of the composite procedure, and identifies the potential to provide hog producers and market participants with accurate expected price probability distributions that can facilitate decision making.

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