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Regional Acreage Response by Quarter for Fresh Tomatoes: An Example of the Use of Mixed Estimation

Published online by Cambridge University Press:  28 April 2015

Michael D. Hammig*
Affiliation:
Fruits, Vegetables, and Sweeteners, National Economics Division, ESCS, USDA

Extract

The study reported was motivated by a USDA study to develop complete quarterly models of supply and demand for a selected set of fresh salad vegetables. The acreage planted component enters recursively into both the acreage harvested and yield relations used in many of these models. Consequently, predictions of acreage planted are instrumental in predicting total supply and resulting market equilibrium solutions.

In modeling acreage planted over relevant seasons within four regions, various sources of information can be brought to bear. Obviously, data series on past plantings, costs, and prices provide the foundation of statistical estimation of an acreage response model. However, additional information from previous studies, economic theory, and subjective judgment on the part of the researcher also can be incorporated into the model through the use of the mixed estimation technique developed by Theil and Goldberger [8].

Type
Research Article
Copyright
Copyright © Southern Agricultural Economics Association 1979

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References

[1]Brook, R. and Wallace, T. D.. “A Note on Extraneous Information in Regression,” Journal of Econometrics, Volume 1, 1973, pp. 315316.CrossRefGoogle Scholar
[2]Hammig, M. D.Supply Response and Simulation of Supply and Demand for the U. S. Fresh Vegetable Industry,” unpublished PhD dissertation, Washington State University, 1978.Google Scholar
[3]Jesse, E. V. and Machado, M. J.. Trends in Production and Marketing of California Fresh Market Tomatoes, Division of Agricultural Sciences Bulletin No. 1871, University of California, 1975.Google Scholar
[4]Lin, W.Measuring Aggregate Supply Response Under Instability,” American Journal of Agricultural Economics, Volume 59, 1977, pp. 903907.CrossRefGoogle Scholar
[5]Nerlove, M.Estimates of the Elasticities of Supply of Selected Agricultural Commodities,” Journal of Farm Economics, Volume 38, 1956, pp. 496509.CrossRefGoogle Scholar
[6]Nerlove, M. and Addison, W.. “Statistical Estimation of Long-Run Elasticities of Supply and Demand,” Journal of Farm Economics, Volume 40, 1958, pp. 861880.CrossRefGoogle Scholar
[7]Theil, H.On the Use of Incomplete Prior Information in Regression Analysis,” Journal of the American Statistical Association, Volume 58, 1963, pp. 401414.CrossRefGoogle Scholar
[8]Theil, H. and Goldberger, A. S.. “On Pure and Mixed Statistical Estimation in Economics,” International Economics Review, Volume 2, 1961, pp. 6578.CrossRefGoogle Scholar
[9]Traill, W. B.Risk Variables in Econometric Supply Response Models,” paper presented at American Agricultural Economics Association annual meetings, State College, Pennsylvania, 1976.Google Scholar
[10]Yancey, T. A., Judge, G. G., and Bock, M. E.. “A Mean Square Error Test When Stochastic Restrictions are Used in Regression,” Communications in Statistics, Volume 3, 1974, pp. 755768.CrossRefGoogle Scholar