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Challenging Belief in the Law of Small Numbers


  • Coble, Keith H.
  • Barnett, Barry J.
  • Riley, John Michael


Introduction : The context of row crop risk management continues to grow more complex. While the magnitude of price and yield risk changes over time, the development of sophisticated risk management tools and complex government policies may improve growers’ ability to manage risk -- if these instruments are used correctly. Conversely, these instruments may actually increase risk exposure if used incorrectly. Gone are the days when growers had access only to individual yield insurance and national triggered price programs. In 1996, revenue insurance became available for many crop growers. For most major crops, the acreage covered by revenue insurance now far exceeds that covered by yield insurance. The 2008 farm bill created the complex risk policies of ACRE and SURE (Ubilava et al.). Mitchell et al. argue that ACRE, which subsumed multiple revenue risks and integrated with other risk instruments, was difficult for growers to understand and difficult for county USDA officials to implement. Current farm bill proposals are now focused on various shallow loss programs such as Agricultural Risk Coverage (ARC), Stacked Income Protection Plan (STAX) and Supplemental Coverage Option (SCO) which layer risk protection on top of crop insurance. Thus, producers are likely to continue to be confronted with complex risk management tools which may overlap or leave gaps in risk protection. Further, the decision becomes even more complex when one considers the possibility of also using futures or forward contracts.

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  • Coble, Keith H. & Barnett, Barry J. & Riley, John Michael, 2013. "Challenging Belief in the Law of Small Numbers," 2013 AAEA: Crop Insurance and the Farm Bill Symposium 156958, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaeaci:156958

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    References listed on IDEAS

    1. Matthew Rabin, 2002. "Inference by Believers in the Law of Small Numbers," The Quarterly Journal of Economics, Oxford University Press, vol. 117(3), pages 775-816.
    2. Mitchell, Paul D. & Rejesus, Roderick M. & Coble, Keith H. & Knight, Thomas O., 2011. "Analyzing Farmer Participation Intentions and Enrollment Rates for the Average Crop Revenue Election (ACRE) Program," Staff Papers 116705, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    3. Anderson, John D. & Harri, Ardian & Coble, Keith H., 2009. "Techniques for Multivariate Simulation from Mixed Marginal Distributions with Application to Whole-Farm Revenue Simulation," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 0(Number 1), pages 1-15, April.
    4. Galarza, Francisco B. & Carter, Michael R., 2010. "Risk Preferences and Demand for Insurance in Peru: A Field Experiment," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61871, Agricultural and Applied Economics Association.
    5. Peterson, Hikaru Hanawa & Tomek, William G., 2007. "Grain Marketing Strategies Within and Across Lifetimes," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 0(Number 1), pages 1-20, April.
    6. Shapira, Zur & Venezia, Itzhak, 2008. "On the preference for full-coverage policies: Why do people buy too much insurance?," Journal of Economic Psychology, Elsevier, vol. 29(5), pages 747-761, November.
    7. Keith H. Coble & Barry J. Barnett, 2013. "Why Do We Subsidize Crop Insurance?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 498-504.
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    Cited by:

    1. Preston, Richard & Walters, Cory G., 2015. "Risk Management Properties of the 2014 Farm Bill," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206435, Agricultural and Applied Economics Association.

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    Agricultural and Food Policy; Risk and Uncertainty;

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