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Incorporating the 1990 Farm Bill into Farm-Level Decision Models: An Application to Cotton Farms

Published online by Cambridge University Press:  28 April 2015

Patricia A. Duffy ,
Danny L. Cain  and
George J. Young
Patricia A. Duffy
Affiliation:
Alabama Agricultural Experiment Station and the Dept. of Agricultural Economics and Rural Sociology at Auburn University, Alabama
Danny L. Cain
Affiliation:
Department of Agricultural Economics and Rural Sociology at Auburn University, Alabama
George J. Young
Affiliation:
Farm Analysis Association of Alabama
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Abstract

A five-year, 0-1, mixed integer programming model was developed to analyze the effects of 1990 Farm Bill legislation on the crop-mix decisions made on cotton farms. Results showed that, when compared to the 1985 Farm Bill, the 1990 Farm Bill can result in higher whole-farm income despite new "triple base" provisions limiting payment acres. The increase in income results from elimination of limited cross-compliance provisions and the change to a three-year base calculation. The model was also used to assess the likely impact of possible changes in the current legislation.

Keywords

cotton farmsfarm programsprogramming models
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 25 , Issue 2 , December 1993 , pp. 119 - 133
Copyright
Copyright © Southern Agricultural Economics Association 1993

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References

Alabama Cooperative Extension Service. 1992 Alabama Crop Enterprise Budgets.Google Scholar
Atwood, J.A., Watts, M.J., and Helmers, G.A.. “Chance-Constrained Financing as a Response to Financial Risk.” Amer. J. Agr. Econ. 70(1988):79–89.CrossRefGoogle Scholar
Cain, D. “Acreage and Farm Program Participation Decisions Made on Alabama Cotton Farms under the 1990 Farm Bill.” Unpublished M.S. Thesis. Auburn University, 1992.Google Scholar
Duffy, P.A., and Taylor, C.R.. “Long-Term Planning on a Corn-Soybean Farm: A Dynamic Programming Analysis.” Agricultural Systems. 42(1993): 57–71.CrossRefGoogle Scholar
Gillespie, J.M., Hatch, L.U., and Duffy, P.A.. “Effect of the 1985 Farm Bill Provisions on Farmers' Soil Conservation Decisions.” S.J. Agr. Econ. 22,2(1990): 179–189.Google Scholar
Lin, W., Dean, G.W., and Moore, C.V.. “An Empirical Test of Utility vs. Profit Maximization in Agricultural Production.” Amer. J. Agr. Econ. 56(1974):497–508.CrossRefGoogle Scholar
Knowles, G.J. “Estimating Utility of Gain Functions for Southwest Minnesota Farmers.” Ph.d. Thesis, University of Minnesota, 1979.Google Scholar
Mims, A.M., Duffy, P.A., and Young, G.. “Effects of Alternative Acreage Restriction Provisions on Alabama Cotton Farms.” S. J. Agr. Econ. 21,2(1989):85–94.Google Scholar
Perry, G.M. “Toward a Holistic Approach to the Cropping Mix Decision.” Unpublished Doctoral Dissertation. Texas A&M University, 1986.Google Scholar
Perry, G.M., McCarl, B., Rister, M.E., and Richardson, J.W.. “Modeling Government Program Participation Decisions at the Farm Level.” Amer. J. Agr. Econ. 71(1989):1011–1020.CrossRefGoogle Scholar
Richardson, J.W. and Nixon, C.J.. A Description of FLIPSIM: A General Firm Level Policy Simulation Model. Bulletin no. b-1528, The Texas Agricultural Experiment Station. College Station, TX. July, 1986.Google Scholar
Tauer, Loren W. “Target MOTAD.” Amer. J. Agr. Econ. 65(1983):6–6-610.CrossRefGoogle Scholar
Wilson, P.N. “Structural Determinants of the Swine Production Industry: A Stochastic Dominance Analysis.” Ph.D. Thesis, University of Minnesota, 1982.Google Scholar