Forecasting livestock prices: Fixed and stochastic coefficients estimation comparisons

Roger K. Conway, Charles B. Hallahan, Richard Stillman and Paul T. Prentice
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Roger K. Conway: Leader of the Productivity and Public Policy Research Section, Resources and Technology Division, Economic Research Service (ERS), US Department of Agriculture (USDA), Postal: Leader of the Productivity and Public Policy Research Section, Resources and Technology Division, Economic Research Service (ERS), US Department of Agriculture (USDA)
Charles B. Hallahan: Agency Systems Branch, Data Services Center, ERS, USDA, Postal: Agency Systems Branch, Data Services Center, ERS, USDA
Paul T. Prentice: General partner of Farm Sector Economics Associates, Postal: General partner of Farm Sector Economics Associates

Agribusiness, 1990, vol. 6, issue 1, 15-32

Abstract: Agricultural commodity analysts have systematically overpredicted livestock prices during the 1980s by using econometric forecasting models that do not account for changing economic conditions. This article compares the out-of-sample forecast performance of the Swamy-Tinsley stochastic coefficients model with ordinary least squares, Cochrane-Orcutt, and maximum likelihood procedures that estimate red meat and chicken prices. The ability of a stochastic coefficients model to adapt quickly to changing economic conditions helps make it almost uniformly superior to a fixed coefficients model in forecasting the quarterly retail price for beef and chicken. The Cochrane-Orcutt and maximum-likelihood procedures appear to forecast pork prices better.

Date: 1990
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Persistent link: https://EconPapers.repec.org/RePEc:wly:agribz:v:6:y:1990:i:1:p:15-32

DOI: 10.1002/1520-6297(199001)6:1<15::AID-AGR2720060103>3.0.CO;2-L

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