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Developing Variable Unit-Structure Premium Rate Differentials in Crop Insurance

Author

Listed:
  • Thomas O. Knight
  • Keith H. Coble
  • Barry K. Goodwin
  • Roderick M. Rejesus
  • Sangtaek Seo

Abstract

Federal crop insurance programs offer producers the option of insuring farm units individually or as an aggregate unit. Existing programs offer a fixed 10% discount for most growers taking coverage at the aggregate level. This article describes an analysis of risk changes when units are aggregated. The methods described here, which base unit aggregation discounts on observable farm characteristics, are approved for implementation into the Federal Crop Insurance Program. Copyright 2010, Oxford University Press.

Suggested Citation

  • Thomas O. Knight & Keith H. Coble & Barry K. Goodwin & Roderick M. Rejesus & Sangtaek Seo, 2010. "Developing Variable Unit-Structure Premium Rate Differentials in Crop Insurance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 141-151.
    • Handle: RePEc:oup:ajagec:v:92:y:2010:i:1:p:141-151
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    File URL: http://hdl.handle.net/10.1093/ajae/aap002
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    Citations

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    Cited by:

    1. Rejesus, R. & Park, S. & Zheng, X. & Goodwin, G., 2018. "How does a Fraud Mitigation Program Influence Insurance Claims filing Behavior? Evidence from the "Spot Check List" Program in U.S. Crop Insurance," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277452, International Association of Agricultural Economists.
    2. Zulauf, Carl R. & Demircan, Vecdi & Scnhitkey, Gary & Barnaby, Glenn Arthur, Jr. & Ibendahl, Gregg & Herbel, Kevin, 2013. "Examining Contemporaneous Farm and County Losses Using Farm Level Data," 2013 AAEA: Crop Insurance and the Farm Bill Symposium 157812, Agricultural and Applied Economics Association.
    3. 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).
    4. Roderick M. Rejesus & Barry K. Goodwin & Keith H. Coble & Thomas O. Knight, 2010. "Evaluation of the reference yield calculation method in crop insurance," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 70(3), pages 427-445, November.
    5. 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.
    6. 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.
    7. Sungkwol Park & Barry K. Goodwin & Xiaoyong Zheng & Roderick M. Rejesus, 2020. "Contract elements, growing conditions, and anomalous claims behaviour in U.S. crop insurance," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(1), pages 157-183, January.
    8. Benjiang Ma & Qing Tang & Yifang Qin & Muhammad Farhan Bashir, 2021. "Policyholder cluster divergence based differential premium in diabetes insurance," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(7), pages 1793-1807, October.
    9. Juan He & Roderick Rejesus & Xiaoyong Zheng & Jose Yorobe, 2018. "Advantageous Selection in Crop Insurance: Theory and Evidence," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 646-668, September.

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