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Payments under the Average Crop Revenue Program: Implications for Government Costs and Producer Preferences

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  • Cooper, Joseph C.

Abstract

This paper develops a stochastic model for comparing payments to U.S. corn producers under the U.S. Senate’s Average Crop Revenue Program (ACR) versus payments under the price-based marketing loan benefit and countercyclical payment programs. Using this model, the paper examines the sensitivity of the density function for payments to changes in expected price levels. We also assess the impact of the choice of yield aggregation used in the ACR payment rate on the mean and variance of farm returns. We find that ACR payments lower the producer’s coefficient of variation of total revenue more than does the price-based support, although ACR may not raise mean revenue as much. While corn farmers in the heartland states might still prefer to receive the traditional forms of support when prices are low relative to statutory loan rates and target prices, this outcome is not necessarily the case for farmers in peripheral production regions.

Suggested Citation

  • Cooper, Joseph C., 2009. "Payments under the Average Crop Revenue Program: Implications for Government Costs and Producer Preferences," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 38(1), April.
  • Handle: RePEc:ags:arerjl:49864
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    References listed on IDEAS

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    1. David A. Hennessy, 1998. "The Production Effects of Agricultural Income Support Policies under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 46-57.
    2. Anton, Jesus & Mouel, Chantal Le, 2004. "Do counter-cyclical payments in the 2002 US Farm Act create incentives to produce?," Agricultural Economics, Blackwell, vol. 31(2-3), pages 277-284, December.
    3. Barry J. Barnett & Dmitry V. Vedenov, 2007. "Is There a Viable Market for Area-Based Crop Insurance?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(2), pages 508-519.
    4. Babula, Ronald A. & Ruppel, Fred J. & Bessler, David A., 1995. "U.S. corn exports: the role of the exchange rate," Agricultural Economics, Blackwell, vol. 13(2), pages 75-88, November.
    5. Barry K. Goodwin & Ashok K. Mishra, 2006. "Are “Decoupled” Farm Program Payments Really Decoupled? An Empirical Evaluation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 73-89.
    6. Fenton, Victor M. & Gallant, A. Ronald, 1996. "Qualitative and asymptotic performance of SNP density estimators," Journal of Econometrics, Elsevier, vol. 74(1), pages 77-118, September.
    7. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
    8. Paolo Sckokai & Daniele Moro, 2006. "Modeling the Reforms of the Common Agricultural Policy for Arable Crops under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 43-56.
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    Cited by:

    1. Woolverton, Andrea E. & Edwin, Young, 2009. "Factors Influencing ACRE Program Enrollment," Economic Research Report 55954, United States Department of Agriculture, Economic Research Service.
    2. Cooper, Joseph C., 2009. "Economic Aspects of Revenue-Based Commodity Support," Economic Research Report 55838, United States Department of Agriculture, Economic Research Service.
    3. Cooper, Joseph C. & Langemeier, Michael R. & Schnitkey, Gary D. & Zulauf, Carl R., 2009. "Constructing Farm Level Yield Densities from Aggregated Data: Analysis and Comparison of Approaches," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49216, Agricultural and Applied Economics Association.
    4. Joseph Cooper & Carl Zulauf & Michael Langemeier & Gary Schnitkey, 2012. "Implications of within county yield heterogeneity for modeling crop insurance premiums," Agricultural Finance Review, Emerald Group Publishing, vol. 72(1), pages 134-155, May.

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