Empirical Evaluation of the Relative Forecasting Performances of Fixed and Varying Coefficient Demand Models

The forecast performances of the fixed coefficient demand model are compared with those of spline function and the Cooley-Prescott varying parameter demand models using consumption and price data for beef, pork, chicken and turkey. In general, the varying parameter models outperformed the fixed coefficient model and the spline function varying parameter model appears to be slightly superior to the Cooley-Prescott model. However, no single model was consistently superior over all the commodities in the capacity to predict either the turning points or commodity levels. Apparently, the explicit specification of structural change using spline rather than random coefficient model offers some improvement in commodity forecasting.


Issue Date:
1983-07
Publication Type:
Working or Discussion Paper
PURL Identifier:
http://purl.umn.edu/117654
Total Pages:
16
Series Statement:
Working Paper
070183




 Record created 2017-04-01, last modified 2017-08-26

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