Vector Autoregression Forecasting Models: Recent Developments Applied to the U.S. Hog Market

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Abstract
Bayesian estimation and the exclusion of variables are two basic approaches to the improvement of vector autoregression forecasting models. This study presents a method which combines and extends several techniques within the exclusion‐of‐variables approach. Several quarterly hog market models are estimated and out‐of‐sample forecasts from 1977 through 1984 are evaluated. The results suggest the proposed method compares favorably to other exclusion‐of‐variables techniques as well as to the more sophisticated bayesian approaches.

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