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Spatial Pattern of Yield Distributions: Implications for Crop Insurance

Author

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  • Francis Annan
  • Jesse Tack
  • Ardian Harri
  • Keith Coble

Abstract

Crop insurance is similar to flood and hurricane insurance in that spatially correlated weather tends to cause violations of the independence assumption. Ideally, one would seek to pool uncorrelated risk drawn from the same distribution in crop insurance. This article proposes a testing procedure for the cross-sectional pooling of group units, and empirically analyzes whether the proposed test improves out-of-sample rating performance. We utilize a balanced panel of U.S. county-level corn yields for 510 counties, and the results of an out-of-sample crop insurance rating performance exercise provide economic significance to the proposed pooling methodology and results.

Suggested Citation

  • Francis Annan & Jesse Tack & Ardian Harri & Keith Coble, 2014. "Spatial Pattern of Yield Distributions: Implications for Crop Insurance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(1), pages 253-268.
    • Handle: RePEc:oup:ajagec:v:96:y:2014:i:1:p:253-268.
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    File URL: http://hdl.handle.net/10.1093/ajae/aat085
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    Citations

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    Cited by:

    1. Regmi, Madhav & Tack, Jesse B., 2018. "Does Crop Insurance Enrollment Exacerbate the Negative Effects of Extreme Heat? A Farm-level Analysis," 2018 Annual Meeting, August 5-7, Washington, D.C. 274468, Agricultural and Applied Economics Association.
    2. Francis Tsiboe & Jesse Tack, 2022. "Utilizing Topographic and Soil Features to Improve Rating for Farm‐Level Insurance Products," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(1), pages 52-69, January.
    3. Yong Liu & Alan P. Ker, 2021. "Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 231-257, March.
    4. Liu, Y. & Ker, A., 2018. "Is There Too Much History in Historical Yield Data," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277293, International Association of Agricultural Economists.
    5. Ker, Alan. P & Tolhurst, Tor & Liu, Yong, 2015. "Rating Area-yield Crop Insurance Contracts Using Bayesian Model Averaging and Mixture Models," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205211, Agricultural and Applied Economics Association.
    6. Wyatt Thompson & Joe Dewbre & Patrick Westfhoff & Kateryna Schroeder & Simone Pieralli & Ignacio Perez Dominguez, 2017. "Introducing medium-and long-term productivity responses in Aglink-Cosimo," JRC Research Reports JRC105738, Joint Research Centre.
    7. Park, Eunchun & Harri, Ardian & Coble, Keith H., 2022. "Estimating Crop Yield Densities for Counties with Missing Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 47(3), September.
    8. Kuangyu Wen, 2023. "A semiparametric spatio‐temporal model of crop yield trend and its implication to insurance rating," Agricultural Economics, International Association of Agricultural Economists, vol. 54(5), pages 662-673, September.
    9. Perloff, Jeffrey M. & Schlenker, Wolfram & Sears, Molly & Wu, Ximing, 2020. "Crop Failures from Temperature and Precipitation Shocks: Implications for U.S. Crop Insurance," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304540, Agricultural and Applied Economics Association.
    10. Park, Eunchun & Brorsen, Wade & Harri, Ardian, 2017. "Spatially Smoothed Crop Yield Density Estimation: Physical Distance vs Climate Similarity," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259145, Agricultural and Applied Economics Association.
    11. Yaoyao Wu & Hanqi Liao & Lei Fang & Guizhen Guo, 2023. "Quantitative Study on Agricultural Premium Rate and Its Distribution in China," Land, MDPI, vol. 12(1), pages 1-14, January.
    12. Jesse Tack & Keith H. Coble & Robert Johansson & Ardian Harri & Barry J. Barnett, 2019. "The Potential Implications of “Big Ag Data” for USDA Forecasts," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(4), pages 668-683, December.
    13. Diao Panpan & Zhang Zhonggen, 2015. "Premium Rate Design and Risk Regionalization for the Policy-Based Wheat Insurance of Henan Province in China," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 9(2), pages 203-229, July.

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