中国农业气象 ›› 2025, Vol. 46 ›› Issue (01): 23-37.doi: 10.3969/j.issn.1000-6362.2025.01.003

• 农业气象保险专刊 • 上一篇    下一篇

牧草干旱天气指数保险产品设计与费率厘定:以果洛州为例

朱彩霞,秦涛,孙浩琳   

  1. 北京林业大学经济管理学院,北京 100083
  • 收稿日期:2023-12-22 出版日期:2025-01-20 发布日期:2025-01-16
  • 作者简介:朱彩霞,E-mail:18137829506@163.com
  • 基金资助:
    北京林业大学中央高校基本科研业务费项目“森林保险支持乡村振兴作用机制与实现路径研究”(2023SKY03);国家社科基金后期资助项目“中国森林保险需求与供给模式研究”(20FGLB022);北京市社会科学基金项目“北京市公益林保险产品创新与运行模式优化”(18YJB011)

Designing Drought Weather Index Insurance for Forage and Determining Premium Rates: A Case Study in Guoluo Prefecture

ZHU Cai-xia, QIN Tao, SUN Hao-lin   

  1. College of Economics and Management, Beijing Forestry University, Beijing 100083, China
  • Received:2023-12-22 Online:2025-01-20 Published:2025-01-16

摘要:

根据2003-2017年果洛州年降水量和牧草单产数据,选取降水距平百分率(Precipitation anomaly in percentage,PA)构建干旱指数(DIq),采用Hodrick prescott filter(HP滤波)方法测算牧草趋势产量从而计算减产率(YLRq),利用固定效应模型拟合牧草干旱指数与单产减产率的相关关系,最后构建损失率期望值模型,实现牧草干旱天气指数保险产品的设计,并厘定保险纯费率。结果表明:1)果洛州牧草干旱致灾危险性呈东南向西北逐渐增加的空间分布特征,其中玛多县为干旱致灾危险性高值区,应重点加强干旱防范;(2)2003−2017年果洛州6个县牧草单产均呈波动上升趋势,其中班玛县牧草单产最高,15a平均单产为11126.67kg·hm2;(3)果洛州牧草干旱指数(DIq)与减产率(YLRq)呈显著的线性相关关系,即YLRq=0.311DIq+0.035(P<0.050),干旱指数每增加一单位,牧草减产率增加0.311个百分点,当干旱指数为0时,其他因素导致牧草减产3.500%;(4)通过EasyFit软件筛选干旱指数概率分布最优模型,分别给出果洛州6个县牧草干旱指数的4种最优分布函数,即Gen.Pareto模型、Error模型、Johnson SB模型和Gen. Extreme Value模型,且Anderson Darling(A−D)检验统计量均小于0.3。果洛州各县牧草轻旱、中旱、重旱与特旱发生概率分别处于8.750%~30.350%13.000%~34.530%、0~13.790%和0~0.820%;(5)果洛州牧草干旱天气指数保险产品在100%保障水平下,6个县纯费率在2.259%~3.748%波动,西北部玛多县的纯费率最高,为3.748%,东南部达日县纯费率最低,为2.259%,牧草干旱天气指数保险纯费率呈东南向西北逐渐增大的空间分布格局。根据果洛州牧草空间分布及干旱情况,建议保险纯费率较高的玛多县、玛沁县等地区可作为试点先行县,制定差异化保费财政补贴政策。

关键词: 牧草保险, 干旱天气指数, 产品设计, 费率厘定, 果洛州

Abstract:

By utilizing annual precipitation and forage yield per unit area data in Guoluo prefecture from 2003 to 2017, the drought weather index (DIq) was constructed by selecting the percentage of precipitation anomaly (PA), the yield loss rate (YLRq) was calculated by employing the Hodrick prescott filter (HP filter) method to estimate the trend yield of pastures, the correlation between the drought index and the pasture yield loss rate was fitted using a fixed-effects model, finally, to establish a loss rate expectation value model. Enabling the design of forage drought weather index insurance product and facilitating the determination of the pure insurance premium rate. The results clearly demonstrated that: (1) the risk of drought-related disasters affecting forage in Guoluo prefecture had a spatial distribution characteristic, increasing progressively from southeast to northwest. Specifically, with Maduo county being high-risk area that required focused attention on drought prevention. (2) From 2003 to 2017, the average forage yield per unit area in the six counties of Guoluo prefecture showed a fluctuating upward trend. Banma county had the highest average yield, averaging an impressive 11126.67kg·ha1 over the 15 years period. (3) There was a significant P<0.050linear relationship between the drought index (DIq) and the forage yield loss rate (YLRq), expressed by the equation YLRq=0.311DIq+0.035P<0.050. Consequently, each unit increase in the DIq resulted in a 0.311 percentage points increase in the forage YLRq. When the DIq was 0, other factors lead to a 3.500% reduction in forage yield. (4) Using the EasyFit software to analyze the probability distribution models of the drought index, four distinct distribution functions were identified for the forage drought index across in the six counties of Guoluo prefecture: Generalized Pareto, Error, Johnson SB, and Generalized Extreme Value models. The AndersonDarling (AD) test statistics confirmed the goodness of fit for all models, the AD test statistics were all less than 0.3. The probability of encountering mild, moderate, severe, and extreme drought conditions in each county of Guoluo prefecture were found to range between 8.750% and 30.350%, 13.000% and 34.530%, 0 and 13.790%, and 0 and 0.820%, respectively. (5) With 100% guarantee level provided by the forage drought weather index insurance product in Guoluo prefecture, the pure premium rates for the forage drought weather index insurance product in the six counties of Guoluo prefecture ranged from 2.259%3.748%, with the highest pure rate of 3.748% in Maduo county in the northwest and the relatively lowest rate of 2.259% in Dari county. The spatial distribution pattern of pure premium rates for pasture drought weather index insurance gradually increased from southeast to northwest. Based on the spatial distribution of pastures and drought conditions in Guoluo prefecture, it was recommended that counties with higher pure premium rates, such as Maduo and Maqin, be considered as pilot counties to implement differentiated fiscal subsidy policies for insurance premiums.

Key words: Forage insurance, Drought weather index, Product design, Premium rate determination, Guoluo prefecture