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Forecasting Agricultural Prices Using a Bayesian Composite Approach

Published online by Cambridge University Press:  28 April 2015

Christopher S. McIntosh  and
David A. Bessler
Christopher S. McIntosh
Affiliation:
Agricultural Economics at the University of Georgia
David A. Bessler
Affiliation:
Agricultural Economics at Texas A&M University
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Abstract

Forecast users and market analysts need quality forecast information to improve their decision-making abilities. When more than one forecast is available, the analyst can improve forecast accuracy by using a composite forecast. One of several approaches to forming composite forecasts is a Bayesian approach using matrix beta priors. This paper explains the matrix beta approach and applies it to three individual forecasts of U.S. hog prices. The Bayesian composite forecast is evaluated relative to composites made from simple averages, restricted least squares, and an adaptive weighting technique.

Keywords

composite forecastingBayesianmatrix betaoutperformance
Type
Submitted Articles
Information
Journal of Agricultural and Applied Economics , Volume 20 , Issue 2 , December 1988 , pp. 73 - 80
Copyright
Copyright © Southern Agricultural Economics Association 1988

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