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Premium Rate Design and Risk Regionalization for the Policy-Based Wheat Insurance of Henan Province in China

Author

Listed:
  • Diao Panpan
  • Zhang Zhonggen

    (School of Management, Zhejiang University, Hangzhou, Zhejiang, China)

Abstract

The policy-based insurance has an important significance to guarantee wheat production, maintain food security and stabilize farmers’ incomes. Pricing for wheat insurance and the risk regionalization are the basis for the smooth development of wheat insurance, especially for Henan province which is the largest wheat production area of China. Therefore, first, the premium rate is calculated using parametric method. Second, the comprehensive wheat production risk scores of all cities in Henan province are calculated through factor analysis, considering the risk exposure in wheat production, the local government’s financial supporting ability, farmers’ economic ability and expected yield loss rate. In addition, the cities are regionalized with method of cluster analysis as well. In addition, it brings out some suggestions to promote the development of policy-based wheat insurance of Henan province.

Suggested Citation

  • 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.
    • Handle: RePEc:bpj:apjrin:v:9:y:2015:i:2:p:203-229:n:4
    DOI: 10.1515/apjri-2014-0028
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    References listed on IDEAS

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    1. Chen, Shu-Ling & Miranda, Mario J., 2004. "Modeling Multivariate Crop Yield Densities With Frequent Extreme Events," 2004 Annual meeting, August 1-4, Denver, CO 19970, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Vincent H. Smith & Joseph W. Glauber, 2012. "Agricultural Insurance in Developed Countries: Where Have We Been and Where Are We Going?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 34(3), pages 363-390.
    3. Olivier Mahul & Charles J. Stutley, 2010. "Government Support to Agricultural Insurance : Challenges and Options for Developing Countries," World Bank Publications - Books, The World Bank Group, number 2432, December.
    4. Richards, Timothy J., 2000. "A Two-Stage Model Of The Demand For Specialty Crop Insurance," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(1), pages 1-18, July.
    5. Mohammed, M.A. & Ortmann, Gerald F., 2005. "Factors influencing adoption of livestock insurance by commercial dairy farmers in three Zobatat of Eritrea," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 44(2), pages 1-15, June.
    6. Barry K. Goodwin, 1993. "An Empirical Analysis of the Demand for Multiple Peril Crop Insurance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(2), pages 425-434.
    7. Vitor A. Ozaki & Sujit K. Ghosh & Barry K. Goodwin & Ricardo Shirota, 2008. "Spatio-Temporal Modeling of Agricultural Yield Data with an Application to Pricing Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 951-961.
    8. 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.
    9. Octavio A. Ramírez, 1997. "Estimation and Use of a Multivariate Parametric Model for Simulating Heteroskedastic, Correlated, Nonnormal Random Variables: The Case of Corn Belt Corn, Soybean, and Wheat Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 191-205.
    10. Botzen, W.J.W. & van den Bergh, J.C.J.M., 2012. "Risk attitudes to low-probability climate change risks: WTP for flood insurance," Journal of Economic Behavior & Organization, Elsevier, vol. 82(1), pages 151-166.
    11. Vincent H. Smith & Joseph W. Glauber, 2012. "Agricultural Insurance in Developed Countries: Where Have We Been and Where Are We Going?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 34(3), pages 363-390.
    12. Zhu, Ying & Goodwin, Barry K. & Ghosh, Sujit K., 2011. "Modeling Yield Risk Under Technological Change: Dynamic Yield Distributions and the U.S. Crop Insurance Program," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 36(1), pages 1-19, April.
    13. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
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