《保险研究》20230102-《种植业保险保障贡献：模型与方法》（王克、张夏、张峭、徐洋）

［摘   要］合理有效评估我国种植业保险对参保作物损失的保障作用，对正确认识我国种植业保险发展水平，推进种植业保险高质量发展具有重要意义。测算种植业保险的损失保障作用，关键在于科学测算参保作物的损失。由于缺少小尺度区域作物单产数据，使得与参保作物尺度相匹配的损失难以被准确测算。本文提出一种基于“细胞分裂”模式的作物期望损失测算模型，在大尺度区域作物单产损失的基础上，通过模拟的方式获取小尺度区域作物期望单产损失，进而测算种植业保险对参保作物损失的保障贡献。以河南小麦和新疆棉花为例，验证了本方法具有可行性；测算的结果与调研数据吻合，也表明测算的种植业保险保障贡献数据具有信度。研究还发现，赔付率和保障深度这两个指标均高估了种植业保险对参保作物损失的保障程度。

［关键词］种植业保险；保障贡献；空间加总偏差；期望损失；“细胞分裂”

［基金项目］国家自然科学基金项目“农业保险保障水平提升的机理和路径研究：合约设计的视角”(72073132)。

［作者简介］王克，博士，中国农业再保险股份有限公司；张夏，博士，中国海油集团能源经济研究院；张峭，博士，中国农业科学院农业信息研究所研究员；徐洋（通讯作者），中国农业科学院农业信息研究所硕士研究生。

The Protection Function of Planting Insurance:Model and Method

WANG Ke,ZHANG Xia,ZHANG Qiao,XU Yang

Abstract：A reasonable and effective evaluation of the protection effect of China′s planting insurance on the loss of insured crops is of great significance to correctly understand the development level of China′s planting insurance and promotes the high-quality development of planting insurance.The key to measure the loss protection function of planting insurance is to scientifically measure the loss of insured crops.It is difficult to accurately measure the loss matching the insured crop scale due to the lack of small-scale regional crop yield data.In this paper,a model of crop expected loss measurement based on the “cell division” model is proposed.On the basis of the large-scale regional crop unit loss,the small-scale regional crop expected loss is obtained through simulation,then the protection function of planting insurance to the insured crop loss is estimated.Taking wheat in Henan and cotton in Xinjiang as examples,the method has been verified to be feasible.It also shows that the protection function data calculated in this paper is credible because the results are consistent with the survey data.In addition,the study also finds that the indicators of claims rate and protection depth of planting insurance overestimate the degree of protection of planting insurance against crop yield loss.

Key words：planting insurance;protection function;data aggregation bias;expected loss;“cell division”