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Measurement of Allocative Biases of Production Control Policies

Published online by Cambridge University Press:  28 April 2015

Robert D. Weaver
Robert D. Weaver*
Affiliation:
College of Agriculture, The Pennsylvania State University
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Extract

Because of growing stocks of grain and the reinstitution of production controls, the question of what allocative impacts such controls imply is once again relevant. The prospect that restrictions on land use may initiate an intensification in the use of substitute inputs such as fertilizer, which are already high in price, is discouraging. Although the issue is an old one, empirical evidence on the extent of these effects is incomplete.1 The purpose of this article is to derive a convenient means of measuring the allocative effects of changes in input restrictions. As an example of empirical application, results are presented which indicate the impact of acreage restrictions during the marketing quota years in North and South Dakota.

Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 10 , Issue 2 , December 1978 , pp. 87 - 91
Copyright
Copyright © Southern Agricultural Economics Association 1978

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References

[1]Allen, R. D. G.Mathematical Analysis for Economists. New York: St. Martin's Press, Inc., 1938.Google Scholar
[2]Beringer, C. “Estimating Enterprise Production Functions From Input-Output Data on Multiple Enterprise Farms,’ ‘Journal of Farm Economics, Volume 39, 1956. pp. 923–930.CrossRefGoogle Scholar
[3]Christensen, R. P. and Aines, R. O.. Economic Effects of Acreage Control Programs in the 1950's. USDA-ERS Agricultural Economics Report No. 18, October 1962.Google Scholar
[4]Christensen, R. P., Jorgenson, D. W., and Lau, L. J.. “Conjugate Duality and the Transcendental Logarithmic Production Function,” Econometrica, Volume 39, July 1971, pp. 255–256.Google Scholar
[5]Gardner, B. L. “Futures Prices in Supply Analysis,” American Journal of Agricultural Economics, Volume 38, 1976, pp. 81–84.CrossRefGoogle Scholar
[6]Griliches, F. “Estimates of the Aggregate Agricultural Production Function From Cross-Sectional Data,” Journal of Farm Economics, Volume 45, May 1963, pp. 419–432.CrossRefGoogle Scholar
[7]Heifner, R. G. “Hedging Potential in Grain Storage and Livestock Feeding,” Agricultural Economic Report 283, Economic Research Service, USD A, 1973.Google Scholar
[8]Hicks, J. R.Value and Capital: An Enquiry Into Some Fundamental Principles of Economic Theory. Oxford, England. Oxford Press, 1939.Google Scholar
[9]Hotelling, H. “Edgeworth's Taxation Paradox and the Nature of Demand and Supply Functions,” Journal of Political Economy, Volume 40, 1932, pp. 577–616.CrossRefGoogle Scholar
[10]Houck, J. P. and Ryan, M. E.. “Supply Analysis for Corn in U.S.: Impact of Changing Government Programs,” American Journal of Agricultural Economics, Volume 54, 1972, pp. 184–191.CrossRefGoogle Scholar
[11]Nerlove, M.The Dynamics of Supply. Baltimore: John Hopkins Press, 1958.Google Scholar
[12]Tyner, F. H. and Tweeten, L. G.. “A Methodology for Estimating Production Functions,” Journal of Farm Economics, Volume 47, 1965, pp. 1462–1467.CrossRefGoogle Scholar
[13]Weaver, R. D.Multiple Product Technologies and Decisions Under Uncertainty and Government Regulation. New York: Academic Press, 1978.Google Scholar
[14]Weaver, R. D. “Measurement of Acreage Response in the Presence of Acreage Control Policies,” 1978 (mimeo).Google Scholar
[15]Weaver, R. D. “Consistent Output and Input Choice Functions for Multiproduct Technologies,” Supply and Input Price Response by Multiple Product Firms: New Approaches AENRS Publication 137, Pennsylvania State University, University Park, Pennsylvania, 1978.Google Scholar
[16]Zellner, A. “An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias,” Journal ofAmerican Statistical Association, June 1962, pp. 585–612.Google Scholar