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U.S. Aggregate Agricultural Production Elasticities Estimated by an Arima Factor Share Adjustment Model

Published online by Cambridge University Press:  28 April 2015

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In an effort to circumvent the multicollinearity problems associated with direct estimation of the aggregate agricultural production function, many economists have used indirect estimation procedures. Because in equilibrium the partial production elasticities of an industry composed of perfectly competitive firms are equal to their respective factor shares, the latter have been used as a means of estimating production elasticities. Most researchers have simply assumed that actual factor shares are equilibrium values (e.g., Griliches; Rosine and Helmberger). Substantive contributions recently have been made in explaining the process of factor share adjustment by changes in prices and technology over time (Binswanger; Lianos). However, except for the work nearly 15 years ago by Tyner and Tweeten (1965), agricultural economics literature is largely silent on the measurement of differences between actual and equilibrium factor shares. It is this issue with which we are primarily concerned in this article. Therefore, our point of departure is the work by Tyner and Tweeten.

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Research Article
Copyright
Copyright © Southern Agricultural Economics Association 1980

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References

Binswanger, H. P.A Cost Function Approach to the Measurement of Elasticities of Factor Demand and Elasticities of Substitution.Amer. J. Agr. Econ. 56(1974):377–86.CrossRefGoogle Scholar
Box, G.E.P. and Jenkins, G. M.. Time Series Analysis: Forecasting and Control, 2nd ed. San Francisco: Holden-Day, 1976.Google Scholar
Griliches, Z.The Demand for Inputs in Agriculture and Derived Supply Elasticity.J. Farm Econ. 41(1959):309–22.CrossRefGoogle Scholar
IMSL. The IMSL Library. Houston: International Mathematical and Statistical Libraries, 1977.Google Scholar
Kmenta, J.Elements of Econometrics. New York: Macmillan Co., 1971.Google Scholar
Lianos, T. P.The Relative Share of Labor in United States Agriculture, 1949-1968.Amer. J. Agr. Econ. 53(1971):411–22.CrossRefGoogle Scholar
Makridakis, S. and Wheelwright, S. C.. Interactive Forecasting Univariate and Multivariate Methods, 2nd ed. San Francisco: Holden-Day, 1978.Google Scholar
Nelson, C. R.Applied Time Series Analysis for Managerial Forecasting. San Francisco: Holden-Day, 1973.Google Scholar
Rosine, J. and Helmberger, P.. “A Neoclassical Analysis of the U.S. Farm Sector, 1948-1970.Amer. J. Agr. Econ. 56(1974):717–29.CrossRefGoogle Scholar
Shumway, C.R., Talpaz, H., and Beattie, B. R.. “The Factor Share Approach to Production Function ‘Estimation’: Actual or Estimated Equilibrium Shares?Amer. J. Agr. Econ. 61(1979): 561–4.CrossRefGoogle Scholar
Tyner, F. H. and Tweeten, L. G.. “A Methodology for Estimating Production Parameters.J. Farm Econ. 47(1965):1462–7.CrossRefGoogle Scholar
Tyner, F. H. and Tweeten, L. G.. “Optimum Resource Allocation in U.S. Agriculture.J. Farm Econ. 48(1966):613–31. Reprinted in A.E.A. Readings in the Economics of Agriculture, K. A. Fox and D. G. Johnson, eds., pp. 286-306. Homewood, Ill.: Richard D. Irwin, Inc., 1969.CrossRefGoogle Scholar
U.S. Department of Agriculture. Farm Income Statistics. Economic Research Service Statistical Bulletin 576, July 1977.Google Scholar
U.S. Department of Agriculture. Farm Income Situation. Economic Research Service, July 1977, July 1965.Google Scholar