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引入标准化降水蒸散指数(SPEI)的区域产量保险定价研究

Research on Area Yield Insurance Rating with Incorporating Standardized Precipitation Evapotranspiration Index(SPEI)

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【作者】 夏梦刘莉熊涛刘笑天

【Author】 XIA Meng;LIU Li;XIONG Tao;LIU Xiao-tian;Chinese Academy of Meteorological Sciences & China Re-catastrophe Risk Management Company Ltd·Joint Open Lab on Meteorological Risk and Insurance;College of Economics and Management, Huazhong Agricultural University;Chinese Academy of Meteorological Sciences;

【通讯作者】 刘笑天;

【机构】 中国气象科学研究院&中再巨灾风险管理股份有限公司.气象风险与保险联合开放实验室华中农业大学经济管理学院中国气象科学研究院

【摘要】 科学合理地厘定保险纯费率是区域产量保险持续、高效发展的基础。区域产量保险定价中纳入气候预测信息是提高保费厘定准确性的重要手段之一。本研究基于美国农业部风险管理局(RiskManagement Agency, RMA)厘定区域产量保险纯费率法,引入标准化降水蒸散指数(Standardizedprecipitation evapotranspiration index,SPEI)构建SPEI-RMA模型,计算东北三省黑龙江、吉林和辽宁的玉米区域产量保险纯费率;引入样本外博弈框架,对比分析SPEI-RMA方法与RMA方法在区域产量保险定价中的表现,以期为设计更精准的区域产量保险产品提供科学依据。结果表明:相较于RMA方法,SPEI-RMA方法拟合作物单产趋势时,黑龙江省、吉林省和辽宁省的决定系数(R2)分别提高了0.044、0.088和0.153,均方误差(MSE)分别降低了0.068、0.067和0.213,有效提高了模型估计精度。利用两种方法厘定三省的纯保费,纯保费的绝对差异值中位数分别为0.105、0.114和0.087。通过样本外博弈发现,在70%、80%和90%的保障水平下,SPEI-RMA方法能更精准厘定保险纯费率,可在经济和统计意义上获得显著收益。

【Abstract】 Developing actuarially fair premium rates is essential for the sustainable and efficient advancement of area yield insurance. Incorporating climate forecast information is one of the important means to enhance the accuracy of premium calculation in area yield insurance pricing. This study introduced the Standardized Precipitation Evapotranspiration Index(SPEI) into the pure premium rate making method of the U.S. Department of Agriculture’s Risk Management Agency(RMA) to construct an SPEI-RMA model. The model was applied to calculate pure premium rates for corn area yield insurance in Heilongjiang, Jilin, and Liaoning provinces of Northeast China. An out-of-sample game framework was employed to compare the performance of the SPEI-RMA method with the traditional RMA method in insurance pricing, aiming to provide a scientific basis for designing more precise area yield insurance products. Results indicated that when fitting the trend of crop yield, compared to the RMA method,the SPEI-RMA method increased the coefficient of determination(R2) by 0.044, 0.088, and 0.153 and reduced the mean squared error(MSE) by 0.068, 0.067, and 0.213 for Heilongjiang, Jilin, and Liaoning, respectively, thereby enhancing model estimation accuracy. The median absolute differences in pure premiums between the two methods are 0.105, 0.114, and 0.087 for the three provinces. Out-of-sample game result revealed that at coverage levels of 70%, 80%, and 90%, the SPEI-RMA method more accurately determines pure premium rates, yielding significant economic and statistical benefits.

【基金】 气象风险与保险联合开放实验室开放基金项目(202300F9);国家自然科学基金青年项目(72203069);国家社会科学基金重大项目(22&ZD079)
  • 【文献出处】 中国农业气象 ,Chinese Journal of Agrometeorology , 编辑部邮箱 ,2025年01期
  • 【分类号】F842.6
  • 【下载频次】10
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