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Forecasting Cattle Prices in the Presence of Structural Change

Published online by Cambridge University Press:  28 April 2015

Barry K. Goodwin
Barry K. Goodwin*
Affiliation:
Department of Agricultural Economics, Kansas State University
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Abstract

Recent empirical research and developments in the cattle industry suggest several reasons to suspect structural change in economic relationships determining cattle prices. Standard forecasting models may ignore structural change and may produce biased and misleading forecasts. Vector autoregressive (VAR) models that allow parameters to vary with time are used to forecast quarterly cattle prices. The VAR procedures are flexible in that they allow the identification of structural change that begins at an a priori unknown point and occurs gradually. The results indicate that the lowest RMSE for out-of-sample forecasts of cattle prices is obtained using a gradually switching VAR model. However, differences between the gradually switching VAR model and a univariate ARIMA model are not strongly significant. Impulse response functions indicate that adjustments of cattle prices to new information have become faster in recent years.

Keywords

cattle pricesmultivariate gradual switching regressionsstructural changetime-varying parameter models
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 24 , Issue 2 , December 1992 , pp. 11 - 22
Copyright
Copyright © Southern Agricultural Economics Association 1992

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