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Multiproduct Production Choices And Pesticide Regulation In Georgia

Published online by Cambridge University Press:  09 September 2016

Christopher S. McIntosh
Affiliation:
Department of Agricultural and Applied Economics, University of Georgia, Athens
Albert A. Williams
Affiliation:
Department of Agricultural and Applied Economics, University of Georgia, Athens

Abstract

An increasing emphasis on surface and groundwater quality and food safety may result in some form of pesticide regulations. A restricted profit function model of Georgia agriculture is used to examine the short-run effects of 2 and 5 percent reductions in all pesticides. Point estimates of short-run impacts, along with their 90 percent confidence intervals are presented.

Type
Articles
Copyright
Copyright © Southern Agricultural Economics Association 1992

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References

Antle, J. M.The Structure of U.S. Agricultural Technology, 1910-78.Am. J. Agr. Econ., 66(1984):414421.Google Scholar
Ball, V. E.Modeling Supply Response in a Multiproduct Framework.Am. J. Agr. Econ., 70(1988):813825.Google Scholar
Batie, S. S.Agriculture as the Problem, The Case of Groundwater Contamination.Choices, Third Quarter, 1988:47.Google Scholar
Chicago Board of Trade. Statistical Annual: Chicago Board of Trade, annual series, 1939-1982.Google Scholar
Cochrane, W. W. and Ryan, M. E.. Am. Farm Policy 1948-1973, Minneapolis, Minnesota: University of Minnesota Press, 1976.Google Scholar
Diewert, W. E.Exact and Superlative Index Numbers.J. Econometrics, 4(1976):115145.Google Scholar
Dorfman, J. H., Kling, C. L. and Sexton, R. J.. “Confidence Intervals for Elasticities and Flexibilities: Re-Evaluating the Ratio of Normals.Am. J. Agr. Econ., 72(1990): 10061017.Google Scholar
Duffy, P. A., Richardson, J. W., and Wohlgenant, M. K.. “Regional CottonAcreage Response.So. J. Agr. Econ., 19(1987):99109.Google Scholar
Evenson, R. State-Level Data Set for U.S. Agriculture 1949-1982, Economic Growth Center, Yale University, New Haven, CN, 1986.Google Scholar
Georgia Department of Natural Resources. Georgia Nonpoint Source Assessment Report, 1988.Google Scholar
Gottret, P. E.A Regional Approach to the Estimation of Multiproduct Input Demand and Output Supply Functions in the U.S.” Ph.D. thesis, Texas A&M University, 1987.Google Scholar
Houck, J. P., Abel, M. E., Ryan, M. E., Gallagher, P. W., Hoffman, R. G., and Penn, J. B.. Analyzing the Impact of Government Programs on Crop Acreage. Washington, D.C.: USDA ERS, Tech. Bull. No. 1548, 1976.Google Scholar
Huffman, W. E., and Evenson, R. E.. “Supply and Demand Functions for Multiproduct U.S. Cash Grain Farms: Biases Caused by Research and Other Policies.Am. J. Agr. Econ., 71(1989):761773.Google Scholar
Knutson, R. D., Taylor, C. R., Penson, J. B., and Smith, E. G. Jr. Economic Impacts of Reduced Chemical Use. College Station, TX: Knutson and Associates, 1990.Google Scholar
Lau, L. J.Applications of Profit Functions,Production Economics: A Dual Approach to Theory and Applications, Vol. 1, Fuss, M. and McFadden, D., eds. Amsterdam: North Holland, 1978.Google Scholar
Lim, H.Profit Maximization, Returns to Scale, Separability, and Measurement Error in State-Level Agricultural Technology.” Ph.D. thesis, Texas A&M University, 1989.Google Scholar
Lopez, R. E.Estimating Substitution and Expansion Effects Using a Profit Function Framework.Am. J. Agr. Econ., 66(1984):358367.Google Scholar
McIntosh, C. S.Specification of Government Policy Variable for Feed Grains, Wheat, Soybeans, Rice, Cotton, Peanuts, Tobacco, Sugar Beets and Milk, 1950-1986.” Dept. Agr. Econ., Faculty Series FS89-61, University of Georgia, 1989(a).Google Scholar
McIntosh, C. S.State Level Data Set for Selected States, 1982-1986.” Dept. Agr. Econ., University of Georgia, unpublished, 1989(b).Google Scholar
McIntosh, C. S.Choosing Among Alternative Methods of Including Government Policy Information for State-Level Multiproduct Agricultural Supply Analysis.” Dept. Agr. Econ., Faculty Series FS90-22, University of Georgia, 1990.Google Scholar
Orazem, P. and Miranowski, J.. “An mdrrect Test for the Specification of Expectation Regimes.Rev. of Econ. and Stat, 68(1986):603609.Google Scholar
Pope, R. D. and Hallam, A.. “Testing the Separability of Production Using Flexible Functional Form Profit Functions.Econ. Letters, 26(1988):265270.Google Scholar
Romain, R.F.J.A Commodity Specific Policy Simulation Model for US Agriculture.” Ph.D. thesis, Texas A&M University, 1983.Google Scholar
Schaub, J.R.Economic Impacts of Chemical Use Reduction on the South: Discussion.So. J. Agr. Econ., 23(1991):2526.Google Scholar
Shideed, K. H. and White, F. C.. “Alternative Forms of Price Expectations in Supply Analysis for U.S. Com and Soybean Acreages.West. J. Agr. Econ., 14(1989):281293.Google Scholar
Shortle, J., and Dunn, J.. “The Relative Efficiency of Agricultural Source and Water Pollution Control Policies.Am. J. Agr. Econ., 68(1986):668677.Google Scholar
Shumway, C. R.Supply, Demand, and Technology in a Multiproduct Industry: Texas Field Crops.Am. J. Agr. Econ., 65(1983):748760.Google Scholar
Shumway, C. R., and Alexander, W. P.. “Agricultural Product Supplies and Input Demands: Regional Comparisons.Am. J. Agr. Econ., 70(1988): 154161.Google Scholar
Silberberg, E.A Revision of Comparative Statics Methodology in Economics, or How to do Comparative Statics on the Back of an Envelope.J.Econ.Theory 7(1974):159172.Google Scholar
Talpaz, H., Alexander, W. P., and Shumway, C. R.. “Estimation of Systems of Equations Subject to Curvature Constraints.J. Stat. Comp. and Sim., 32(1989):201214.Google Scholar
Taylor, C. R., Penson, J. B. Jr., Smith, E. G., and Knutson, R.. “Economic Impacts of Chemical Use Reduction on the South.So. J. Agr. Econ., 23(1991): 1523.Google Scholar
Teigen, L. D., and Singer, F.. Weather in U.S. Agriculture: Monthly Temperature and Precipitation by State and Farm Production Region, 1950-1986. Washington, D.C.:USDA ERS Stat. Bull. No. 765, February 1988.Google Scholar
U.S. Department of Agriculture, Agricultural Stabilization and Conservation Service, Commodity Fact Sheets. Washington, D.C., 1972-1988.Google Scholar
U.S. Department of Agriculture, Agricultural Prices, annual series. Wahsington, D.C.: 1949-1984a.Google Scholar
U.S. Department of Agriculture. Agricultural Statistics, annual series. Wahsington, D.C.: 1949-1988b.Google Scholar
U.S. Department of Agriculture. Feed Situation, ERS annual series. Wahsington, D.C.: 1949-1988c.Google Scholar
U.S. Department of Agriculture. Wheat Situation, ERS annual series Wahsington, D.C.: 1949-1988d.Google Scholar
U.S. Department of Agriculture. State Farm Income and Balance Sheet Statistics, ERS annual series. Wahsington, D.C.: 1949-1988e.Google Scholar
U.S. Department of Agriculture. Meat Animals, Production, Disposition and Income, Crop Reporting Board annual series. Wahsington, D.C.: 1949-1984f.Google Scholar
U.S. Department of Agriculture. Seed Crops, Crop Reporting Board, annual series. Wahsington, D.C.:1949-1984g.Google Scholar
U.S. Department of Agriculture. Farm Labor, Crop Reporting Board, annual series. Wahsington, D.C.: 1949-1984h.Google Scholar
U.S. Economics, Statistics and Cooperatives Service. Field Crop Production, Disposition, and Value, annual series. Wahsington, D.C.: 1949-1984i.Google Scholar
Weaver, R. D.Multiple Input, Multiple Output Production Choices and Technology in the U.S. Wheat Region.Am. J. Agr. Econ., 65(1983):4556.Google Scholar