AbstractAgricultural 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 pr