作物保险非参数纯费率的调整及实证研究

发布时间：2018-06-26 21:03

本文选题：非参数核密度 + 最小叉熵优化模型　；参考：《系统工程》2013年04期

【摘要】：作物保险纯费率的精确厘定依赖于单产分布的正确选择。把非参数分布作为先验分布,同时考虑影响单产分布的矩信息,应用最小叉熵优化模型得到最小叉熵分布,基于最小叉熵分布厘定作物保险纯费率,实现非参数纯费率的调整。把这种方法应用到辽宁四种主要作物上,进行实证分析,得到结论:调整后的费率比未调整的非参数费率都低,解决了非参数费率偏高的问题。最小叉熵分布同时考虑了先验分布和更多关于分布的矩信息,是更合理的作物单产分布,改进了作物保险纯费率厘定的方法,提高了计算结果的合理性与准确性,可以为保险实践提供更有价值的参考。
[Abstract]:The accurate determination of the net rate of crop insurance depends on the correct choice of the distribution of yield per unit yield. Taking the nonparametric distribution as the prior distribution and considering the moment information that affects the distribution of yield, the minimum cross-entropy distribution is obtained by using the minimum cross-entropy optimization model. Based on the minimum cross-entropy distribution, the pure rate of crop insurance is determined, and the adjustment of the non-parametric pure rate is realized. By applying this method to four main crops in Liaoning Province, the conclusion is drawn that the adjusted rate is lower than that of the unadjusted non-parametric rate, which solves the problem that the non-parametric rate is too high. The minimum cross-entropy distribution takes into account both the prior distribution and the moment information about the distribution, which is a more reasonable distribution of crop yield, improves the method of determining the net rate of crop insurance, and improves the rationality and accuracy of the calculation results. It can provide more valuable reference for insurance practice.
【作者单位】：沈阳农业大学经济管理学院;沈阳农业大学理学院;
【基金】：辽宁省重大重点软科学研究计划项目(2009401028)
【分类号】：F840;F326

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