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A Multi-Product Analysis of Energy Demand in Agricultural Subsectors
Published online by Cambridge University Press: 05 September 2016
Abstract
A multi-product cost function model was used to analyze energy demand in various agricultural subsectors. This approach has advantages over previously used approaches since it reduces aggregation bias, considers technological jointness, and provides various disaggregative measures related to energy input demand. When fitted to West Virginia county level data, labor and miscellaneous inputs in crop and livestock production were found to be substitutes for energy, while capital, machinery, and fertilizer were complementary to energy. Energy demand was inelastic and increases in machinery prices had the largest reduction effect on energy demand. Technological change was found to be capital, machinery, and fertilizer using, but it was labor and energy saving. Analyses indicated that the elasticity of demand for energy inputs with respect to livestock output was significantly larger than the elasticity with respect to crop output.
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References
Adelaja, A. O. “An Analysis of Production Technology and Policy in the Multi-Product Cost Function Framework: The Case of West Virginia Agriculture.” Unpublished Ph.D. dissertation, West Virginia University; Morgantown, West Virginia, 1985.Google Scholar
Ball, E. V. and Chambers, R. O.. “An Economic Analysis of Technology in the Milk Products Industry.” Amer. J. Agr. Econ., 64,4(1982):699–709.CrossRefGoogle Scholar
Barten, A. P. “Maximum Likelihood Estimates of a Complete System of Demand Equation.” Europ. Econ. Rev., 1,1(1969):7–73.CrossRefGoogle Scholar
Berndt, E. R. and Wood, D. O.. “Technology, Prices, and Derived Demands for Energy.” Rev. Econ. Stat., 57,3(1975):259–268.CrossRefGoogle Scholar
Binswanger, H. P. “A Cost Function Approach to the Measurement of Factors Demand and Elasticities of Substitution.” Amer. J. Agr. Econ., 56,2(1974):377–386.CrossRefGoogle Scholar
Burgess, D. F. “A Cost Minimization Approach to Import Demand Equations.” Rev. Econ. Stat., 56,2(1974):225–234.CrossRefGoogle Scholar
Christensen, L. R. and Jorgenson, D. W.. “The Measurement of U. S. Real Capital Input, 1929-1967.” Rev. Inc. Wealth, 15,4(1969):293–320.CrossRefGoogle Scholar
Denny, M. and Pinto, C.. “An Aggregate Model with Multi-Product Technologies.” Production Economics: A Dual Approach to Theory and Application.
Amsterdam: North Holland Publishing Co.; 1978.Google Scholar
Denny, M. and Fuss, M.. “The Use of Approximation Analysis to Test for Separability and >the Existence of Consistent Aggregates.” Amer. Econ. Rev., 67,3(1977):404–418.Google Scholar
Diewert, W. E. “An Application of Shephard Duality Theorem: A Generalized Leontief Production Function.”. J. Polit. Econ., 79,3(1971):481–507.CrossRefGoogle Scholar
Griffin, J. M. and Gregory, P. R.. “An Inter-Country Translog Model of Energy Substitution Responses.” Amer. Econ. Rev., 66,5(1976):854–857.Google Scholar
Harper, C. and Field, B. C.. “Energy Substitution in U.S. Manufacturing: A Regional Approach.” So. Econ. J., 50, 2(1983):385–395.CrossRefGoogle Scholar
Hoque, A. and Adelaja, A.. “Factor Demand and Returns to Scale in Milk Production: Effects of Price, Substitution and Technology.” Northeastern J. Agr. Resource Econ., 13, 2(1984):238–245.CrossRefGoogle Scholar
Humphrey, D. and Moroney, J.. “Substitution Among Capital, Labor and Natural Resource Products in American Manufacturing.” J. Polit. Econ., 83,4(1975):57–82.CrossRefGoogle Scholar
Just, R. E., Zilberman, D., and Hochman, E.. “Estimation of Multi-crop Production Functions.” Amer. J. Agr. Econ., 65,4(1983):770–780.CrossRefGoogle Scholar
Kmenta, J. and Gilbert, R.. “Small Sample Properties of Alternative Estimates of Seemingly Unrelated Regressions.” J. Amer. Stat. Assoc., 63,324(1968):1,180–2,000.CrossRefGoogle Scholar
Lopez, R. E..“Analysis of a Small Open Economy: The Case of Energy Prices in Canada.” Amer. J. Agr. Econ., 64,3(1982):510–520.CrossRefGoogle Scholar
McFadden, D. “Estimation Techniques for the Elasticity of Substitution and Other Production Parameters.” Production Economics: A Dual Approach to Theory and Application.
Amsterdam: North Holland Publishing Co.; 1978.Google Scholar
Miranowski, J. A..and Mensah, E. K.. “Derived Demand for Energy in Agriculture: Effects of Price, Substitution and Technology.” paper presented at the annual meetings of the American Agricultural Economics Association, Washington State University; July 29- August 1, 1979.Google Scholar
Ray, S. C. “A Translog Cost Function Analysis of the U. S. Agriculture, 1939-1977.” Amer. J. Agr. Econ., 64,3(1982):490–498.CrossRefGoogle Scholar
Ruble, W. L. “Improving the Computations of Simultaneous Stochastic Linear Equation Estimates.” Unpublished Ph.D. dissertation, Michigan State University, 1968.Google Scholar
Shumway, C. R. “Supply, Demand, and Technology in a Multi-Product Industry: Texas Field Crops.” Amer. J. Agr. Econ., 65,4(1983):748–760.CrossRefGoogle Scholar
Shumway, C. R., Pope, R. D., and Nash, E. K.. “Allocatable Fixed Inputs and Jointness in Agricultural Production: Implications for Economic Modeling.” Amer. J. Agr. Econ., 66, 1(1984):72–78.CrossRefGoogle Scholar
Solow, R. M. “Technical Change and the Aggregate Production Function.” Rev. Econ. Stat., 39,3(1957):312–320.CrossRefGoogle Scholar
U. S. Department of Agriculture. Crop Reporting Board. Agricultural Prices.
Washington, D. C.; December Issues; 1959–1983.Google Scholar
U. S. Department of Agriculture. Agricultural Statistics.
Washington, D. C.; selected years.Google Scholar
U. S. Department of Commerce. Bureau of Census. West Virginia, Census of Agriculture.
Washington, D. C.; 1959, 1964, 1969, 1974, 1978, and 1982 issues.Google Scholar
Zellner, A. “An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests of Aggregation Bias.” J. Amer. Stat. Assoc., 57(1962):585–612.CrossRefGoogle Scholar