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A multi-region approach to assessing fiscal and farm level consequences of government support for farm risk management

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  • Cooper, Joseph
  • Delbecq, Benoît
Abstract
The 2014 U.S. Farm Act has new programs for providing producers with commodity support payments covering “shallow losses” in revenue. We develop an approach to examine the sensitivity of the farmer’s downside risk protection to marginal changes in the deductible in shallow loss program scenarios. The copula approach we use simultaneously considers price and yield correlation across all U.S. counties producing several major field crops. We find that average payments under the shallow loss program scenarios are elastic with respect to the program’s payment coverage rate. To empirically assess where shallow loss is likely to most benefit producers, we map at the county level the ratios of expected shallow loss payments to crop insurance premiums for corn, soybeans, cotton, and winter wheat. As tail dependencies among individual crop yield densities may vary spatially, we propose a method for grouping counties in a t-copula that allows for heterogeneity in tail dependencies.

Suggested Citation

  • Cooper, Joseph & Delbecq, Benoît, 2014. "A multi-region approach to assessing fiscal and farm level consequences of government support for farm risk management," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 3(3), pages 1-23, December.
    • Handle: RePEc:ags:aieabj:196654
    DOI: 10.22004/ag.econ.196654
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    1. Schnitkey, Gary, 2012. "Crop Insurance in 2012," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 2, July.
    2. Effland, Anne & Cooper, Joseph & O'Donoghue, Erik, 2014. "2014 Farm Act Shifts Crop Commodity Programs Away From Fixed Payments and Expands Program Choices," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, issue 06, pages 1-1, July.
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    6. Heimlich, Ralph E., 2000. "Farm Resource Regions," Agricultural Information Bulletins 33625, United States Department of Agriculture, Economic Research Service.
    7. Barry K. Goodwin, 2009. "Payment Limitations and Acreage Decisions under Risk Aversion: A Simulation Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 19-41.
    8. Bouye, Eric & Durlleman, Valdo & Nikeghbali, Ashkan & Riboulet, Gaël & Roncalli, Thierry, 2000. "Copulas for finance," MPRA Paper 37359, University Library of Munich, Germany.
    9. 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.
    10. Arriola, Christine & Dismukes, Robert & Coble, Keith H. & Ubilava, David & Cooper, Joseph C., 2011. "Alternatives to a State-Based ACRE Program: Expected Payments Under a National, Crop District, or County Base," Economic Research Report 262235, United States Department of Agriculture, Economic Research Service.
    11. John S. Lapp & Vincent H. Smith, 1992. "Aggregate Sources of Relative Price Variability Among Agricultural Commodities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 74(1), pages 1-9.
    12. 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.
    13. 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 Limited, vol. 72(1), pages 134-155, May.
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    Cited by:

    1. Eric J Belasco & Joseph Cooper & Vincent H Smith, 2020. "The Development of a Weather‐based Crop Disaster Program," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 240-258, January.
    2. Hungerford, Ashley & O'Donoghue, Erik & Motamed, Mesbah, 2015. "Risk Reduction and the 2014 Farm Bill," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 204845, Agricultural and Applied Economics Association.
    3. Cooper, Joseph & Hungerford, Ashley & O'Donoghue, Erik, 2015. "Interactions of Shallow Loss Support and Traditional Federal Crop Insurance: Building a Framework for Assessing Commodity Support Issues for the Next Farm Act," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205310, Agricultural and Applied Economics Association.
    4. Motamed, Mesbah & Hungerford, Ashley & Rosch, Stephanie & O’Donoghue, Erik & MacLachlan, Matthew & Astill, Gregory & Cessna, Jerry & Joseph Cooper, 2018. "Federal Risk Management Tools for Agricultural Producers: An Overview," Economic Research Report 276229, United States Department of Agriculture, Economic Research Service.
    5. Santeramo, Fabio Gaetano & Maccarone, Irene, 2022. "Analisi storica delle rese agricole e la variabilità del clima: Analisi dei dati italiani sui cereali [Historical crop yields and climate variability: analysis of Italian cereal data]," MPRA Paper 114135, University Library of Munich, Germany, revised 04 Aug 2022.
    6. Hungerford, Ashley & O'Donoghue, Erik, 2016. "Federal Crop Insurance Options for Upland Cotton Farmers and Their Revenue Effects," Economic Research Report 249774, United States Department of Agriculture, Economic Research Service.
    7. Hungerford, Ashley & Astill, Gregory & Effland, Anne, 2017. "Changes to the Noninsured Crop Disaster Assistance Program Under the Agricultural Act of 2014: Their Potential Risk Reduction Impacts," Economic Information Bulletin 262132, United States Department of Agriculture, Economic Research Service.

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    More about this item

    Keywords

    Agricultural and Food Policy; Farm Management; Risk and Uncertainty;
    All these keywords.

    JEL classification:

    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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