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Policy Implications of Crop Yield and Revenue Variability at Differing Levels of Disaggregation

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  • Coble, Keith H.
  • Dismukes, Robert
  • Thomas, Sarah E.

Abstract

Revenue variability at different levels of aggregation has been the focus of several proposals to reform U.S. commodity programs with the 2007 farm bill. In this paper, we estimate revenue variabilityyear-to-year deviations from expected revenue for corn, soybeans, and cotton at four levels of aggregation: national, state, county and farm. We examine the factors that cause revenue variability and how differences across crops and regions would affect producers risks. We find that national-level revenue variability is nearly double national-level yield variability. Spatial disaggregation increases price and yield variability, but yield variability increases more rapidly than price and revenue variability. A hypothetical national-level revenue program would reduce risk at the average farm-level by slightly more than 8 percent for corn, about 7 percent for soybeans and about 21 percent for cotton. If one integrates farm-level revenue coverage with the national-level program the percent risk reduction more than doubles for both corn and soybeans. Although the increase in risk reduction between the simple national and the integrated program is proportionately less for cotton, the total risk reduction for cotton is the greatest among the three crops.

Suggested Citation

  • Coble, Keith H. & Dismukes, Robert & Thomas, Sarah E., 2007. "Policy Implications of Crop Yield and Revenue Variability at Differing Levels of Disaggregation," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon 9759, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea07:9759
    DOI: 10.22004/ag.econ.9759
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    Cited by:

    1. Roger Claassen & Christian Langpap & JunJie Wu, 2017. "Impacts of Federal Crop Insurance on Land Use and Environmental Quality," American Journal of Agricultural Economics, John Wiley & Sons, vol. 99(3), pages 592-613, April.
    2. Maria Osipenko & Zhiwei Shen & Martin Odening, 2015. "Is there a demand for multi-year crop insurance?," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 75(1), pages 92-102, May.
    3. Claassen, Roger & Cooper, Joseph C. & Carriazo, Fernando, 2011. "Crop Insurance, Disaster Payments and Land Use Change: The Effect of Sodsaver on Incentives for Grassland Conversion," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 43(2), pages 1-17, May.
    4. Pigeon, Mathieu & Frahan, Bruno Henry de & Denuit, Michel, 2012. "Actuarial evaluation of the EU proposed farm income stabilisation tool," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122485, European Association of Agricultural Economists.
    5. Keith H. Coble & Robert Dismukes, 2008. "Distributional and Risk Reduction Effects of Commodity Revenue Program Design ," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 30(3), pages 543-553.
    6. Finger, Robert, 2012. "Biases in Farm-Level Yield Risk Analysis due to Data Aggregation," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 61(1).
    7. Claassen, Roger & Carriazo, Fernando & Cooper, Joseph C. & Hellerstein, Daniel & Ueda, Kohei, 2011. "Grassland to Cropland Conversion in the Northern Plains: The Role of Crop Insurance, Commodity, and Disaster Programs," Economic Research Report 262239, United States Department of Agriculture, Economic Research Service.
    8. Huo, Ran & Octavio, Ramirez, 2017. "Basis risk and welfare effect of weather index insurance for smallholders in China," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252816, Southern Agricultural Economics Association.
    9. Jindřich Špička, 2009. "The Risk Analysis in the Agricultural Enterprises using Earnings at Risk Method," Ekonomika a Management, Prague University of Economics and Business, vol. 2009(3).
    10. Elizabeth Nolan & Paulo Santos, 2019. "Genetic modification and yield risk: A stochastic dominance analysis of corn in the USA," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-10, October.
    11. Tiwari, Sweta & Coble, Keith & Harri, Ardian & Barnett, Barry, 2017. "Hedging the Price Risk of Crop Revenue Insurance Through the Options Market," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 253081, Southern Agricultural Economics Association.
    12. Severini, Simone & Tantari, Antonella & Di Tommaso, Giuliano, 2016. "The instability of farm income. Empirical evidences on aggregation bias and heterogeneity among farm groups," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 5(1), pages 1-19, April.
    13. Kleiman, Rachel M. & Characklis, Gregory W. & Kern, Jordan D. & Gerlach, Robin, 2021. "Characterizing weather-related biophysical and financial risks in algal biofuel production," Applied Energy, Elsevier, vol. 294(C).
    14. Pigeon, Mathieu & Henry de Frahan, Bruno & Denuit, Michel, 2014. "Evaluation of the EU Proposed Farm Income Stabilisation Tool by Skew Normal Linear Mixed Models," LIDAM Discussion Papers ISBA 2014003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Pigeon, Mathieu & Henry de Frahan, Bruno & Denuit, Michel, 2012. "Evaluation of the EU proposed Farm Income Stabilisation Tool," LIDAM Discussion Papers ISBA 2012026, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    16. Finger, Robert, 2012. "Biases in Farm-Level Yield Risk Analysis due to Data Aggregation," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 61(01), pages 1-14, February.
    17. Anton, Jesus & Kimura, Shingo, 2009. "Farm Level Analysis of Risk, and Risk Management Strategies and Policies: Evidence from German Crop Farms," 2009 Conference, August 16-22, 2009, Beijing, China 51729, International Association of Agricultural Economists.
    18. Finger, Robert, 2012. "How strong is the “natural hedge”? The effects of crop acreage and aggregation levels," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122538, European Association of Agricultural Economists.
    19. Carriazo, Fernando & Claassen, Roger & Cooper, Joseph C., 2009. "Crop Insurance, Disaster Payments, and Incentives for Land Use Change in Agriculture: A Preliminary Assessment," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49218, Agricultural and Applied Economics Association.
    20. Jindřich Špička & Václav Vilhelm, 2013. "Determinants of the Risk Environment in Agricultural Enterprises in the Czech Republic [Determinanty rizikového prostředí zemědělských podniků v České republice]," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2013(2), pages 69-87.
    21. 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.

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    Keywords

    Agricultural and Food Policy;

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