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The efficiency of composite weather index insurance in hedging rice yield risk: evidence from China

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  • Hong Shi
  • Zhihui Jiang

Abstract

As an economic and market-transparent program, weather index insurance is expected to mitigate asymmetric problem. Capturing the relationship between yield and weather factor(s) is the basis of index insurance, but remains a challenge for weather index schemes. Meanwhile, composite weather index insurance is needed by farmers when their agricultural activities involve several risks, but is rarely studied. We aim to design a composite weather index insurance model and evaluate its efficiency in hedging yield risk by using the case of rice production in China. We divide the whole growth cycle of rice into six stages on the basis of agronomic knowledge, and use the average value of each weather factor in each stage to design a weather index. Then, the efficiency of composite weather index insurance is evaluated by mean-semivariance and value-at-risk methods. First, we find that subdivision of the growth cycle helps to better capture the subtle relationship between rice yield and weather factors. Second, composite weather index insurance evidently reduces yield risk. Our findings help further adoption of weather index insurance in agricultural fields.

Suggested Citation

  • Hong Shi & Zhihui Jiang, 2016. "The efficiency of composite weather index insurance in hedging rice yield risk: evidence from China," Agricultural Economics, International Association of Agricultural Economists, vol. 47(3), pages 319-328, May.
    • Handle: RePEc:bla:agecon:v:47:y:2016:i:3:p:319-328
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    Cited by:

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    2. Qing Sun & Zaiqiang Yang & Xianghong Che & Wei Han & Fangmin Zhang & Fang Xiao, 2018. "Pricing weather index insurance based on artificial controlled experiment: a case study of cold temperature for early rice in Jiangxi, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(1), pages 69-88, March.
    3. Aditya Kusuma & Bethanna Jackson & Ilan Noy, 2018. "A viable and cost-effective weather index insurance for rice in Indonesia," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 43(2), pages 186-218, September.
    4. Md. Bokhtiar Hasan & Md. Delowar Hossain & Abu N.M. Wahid, 2018. "Application of Forward Contract and Crop Insurance as Risk Management Tools of Agriculture: A Case Study in Bangladesh," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 8(12), pages 1394-1405, December.
    5. Mengmeng Qiang & Manhong Shen & Guanjun Xia, 2023. "The effectiveness of weather index insurance in managing mariculture production risk," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(2), pages 245-262, April.
    6. Fan, Qi & Tan, Ken Seng & Zhang, Jinggong, 2023. "Empirical tail risk management with model-based annealing random search," Insurance: Mathematics and Economics, Elsevier, vol. 110(C), pages 106-124.
    7. Zaura Fadhliani & Jeff Luckstead & Eric J. Wailes, 2019. "The impacts of multiperil crop insurance on Indonesian rice farmers and production," Agricultural Economics, International Association of Agricultural Economists, vol. 50(1), pages 15-26, January.
    8. Baoling Zou & Zanjie Ren & Ashok K. Mishra & Stefan Hirsch, 2022. "The role of agricultural insurance in boosting agricultural output: An aggregate analysis from Chinese provinces," Agribusiness, John Wiley & Sons, Ltd., vol. 38(4), pages 923-945, October.
    9. Richard A. Gallenstein & Jon Einar Flatnes & John P. Dougherty & Abdoul G. Sam & Khushbu Mishra, 2021. "The impact of index‐insured loans on credit market participation and risk‐taking," Agricultural Economics, International Association of Agricultural Economists, vol. 52(1), pages 141-156, January.
    10. Zhuoxin Liu & Laijun Zhao & Chenchen Wang & Yong Yang & Jian Xue & Xin Bo & Deqiang Li & Dengguo Liu, 2019. "An Actuarial Pricing Method for Air Quality Index Options," IJERPH, MDPI, vol. 16(24), pages 1-19, December.

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