A Comparison of Forecasting Accuracies of Alternative Regional Production Index Methodologies

This article examines the forecasting accuracies of various methods used by Federal Reserve Banks to estimate real value added by regional manufacturing industries. Using Texas manufacturing data and weighted forecasting accuracy measures consistent with index number construction for Texas, obtained results support the use of very simple methods based on the assumption of product exhaustion, allowing for technical change. More complex methods using Cobb-Douglas production functions estimated by Bayesian techniques did not perform as well, not because of lack of conceptual sophistication or appropriate prior information but probably because of the small number of observations and collinearity of the data that are available when constructing regional production indices. These results must be qualified. The weighted forecasting accuracy measures tend to obscure the fact that no one method is uniformly superior to the other methods for all industries. Given industry weights different from those for Texas, the results presented here could be reversed. Confirmation of the conclusions drawn await the results of other regional manufacturing studies.