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On the Possibility of a Private Crop Insurance Market: A Spatial Statistics Approach

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  • H. Holly Wang
  • Hao Zhang

Abstract

Risk theory tells us if an insurer can effectively pool a large number of individuals to reduce total risk, the insurer can then provide insurance by charging a premium close to the actuarially fair rate. However, a common belief exists that risk can be effectively pooled only when random loss is independent. Therefore crop insurance markets cannot survive without government subsidy because crop yields are not independent among growers. In this article, we take a spatial statistics approach to examine the effectiveness of risk pooling for crop insurance under correlation. We develop a method for evaluating the effectiveness of risk pooling under correlation and apply the method to three major crops in the United States: wheat, soybeans, and corn. The empirical study shows that yields for the three crops present zero or negative correlation when two counties are far apart, which complies with a weaker condition than independence, finite-range positive dependency. The results show that effective risk pooling is possible and reveal a high possibility of a private crop insurance market in the United States. Copyright 2003 The Journal of Risk and Insurance.

Suggested Citation

  • H. Holly Wang & Hao Zhang, 2003. "On the Possibility of a Private Crop Insurance Market: A Spatial Statistics Approach," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 70(1), pages 111-124.
  • Handle: RePEc:bla:jrinsu:v:70:y:2003:i:1:p:111-124
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    Citations

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    Cited by:

    1. Di Falco, Salvatore & Capitanio, Fabian & Adinolfi, Felice, 2011. "Natural Vs Financial Insurance in the Management of Weather Risk Exposure in the Italian Agriculture," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114325, European Association of Agricultural Economists.
    2. Wei Xu & Guenther Filler & Martin Odening & Ostap Okhrin, 2010. "On the systemic nature of weather risk," Agricultural Finance Review, Emerald Group Publishing, vol. 70(2), pages 267-284, August.
    3. Ming Wang & Tao Ye & Peijun Shi, 2016. "Factors Affecting Farmers’ Crop Insurance Participation in China," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(3), pages 479-492, September.
    4. Zhiwei Shen & Martin Odening, 2013. "Coping with systemic risk in index-based crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 44(1), pages 1-13, January.
    5. Ceballos, Francisco, 2016. "Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay," IFPRI discussion papers 1595, International Food Policy Research Institute (IFPRI).
    6. repec:fgv:epgrbe:v:71:y:2017:i:4:a:27375 is not listed on IDEAS
    7. Zhiwei Shen & Martin Odening & Ostap Okhrin, 2016. "Can expert knowledge compensate for data scarcity in crop insurance pricing?," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 43(2), pages 237-269.
    8. Vitor Ozaki, 2009. "Pricing farm-level agricultural insurance: a Bayesian approach," Empirical Economics, Springer, vol. 36(2), pages 231-242, May.
    9. Geoffroy Enjolras & Patrick Sentis, 2008. "The main determinants of insurance purchase. An empirical study on crop insurance policies in France," Working Papers 08-06, LAMETA, Universtiy of Montpellier, revised Apr 2008.
    10. Feng, Xiaoguang & Hayes, Dermot, 2014. "Is Government Involvement Really Necessary: Implications for Systemic Risk and Crop Reinsurance Contracts," 2014 AAEA: Crop Insurance and the 2014 Farm Bill Symposium: Implementing Change in U.S. Agricultural Policy, October 8-9, Louisville, KY 184241, Agricultural and Applied Economics Association.
    11. Ostap Okhrin & Martin Odening & Wei Xu, 2013. "Systemic Weather Risk and Crop Insurance: The Case of China," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(2), pages 351-372, June.
    12. Wang, Xin & Lim, Michael K. & Ouyang, Yanfeng, 2015. "Infrastructure deployment under uncertainties and competition: The biofuel industry case," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 1-15.
    13. Lambert, Dayton M. & Griffin, Terry W., 2004. "Analysis Of Government Farm Subsidies On Farmland Cash Rental Rates Using A Fixed Effect Spatial Distributed Lag Model And A Translog Cost Model," 2004 Annual meeting, August 1-4, Denver, CO 19977, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    14. Lysa Porth & Milton Boyd & Jeffrey Pai, 2016. "Reducing Risk Through Pooling and Selective Reinsurance Using Simulated Annealing: An Example from Crop Insurance," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 41(2), pages 163-191, September.

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