作物保险定价模型与实证研究
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摘要
作物保险是目前“三农”问题的重点之一。农业生产过程中,农户收益面临着自然气候及市场环境变动带来的多种风险。2004年国家开始实施政策性农业保险试点工作以来,我国的农业保险工作有了长足的进展,但是由于现有的政策性农业保险的险种单一、保障率较低且保险额多为农业生产的物化成本等原因,农民的投保积极性并不高。而保险公司方面,由于农业风险一般具有系统性,较低的参保率使得风险无法在较大范围内得到分散；同时农业保险赔付率较高的特点,使得保险公司在推出新的农业保险产品方面的积极性有限。
基于农业保险存在的上述问题,本文借鉴国内外现有研究成果,改进了作物产量保险定价模型,构建了作物收入保险定价模型,并在此基础上开展了实证研究。相关研究成果简述如下：
(1)构建基于非参数核密度方法的作物产量保险定价模型,克服了现有研究中假设作物单产波动服从正态分布而忽视其尖峰、厚尾、有偏性导致的问题；结合安徽、北京、福建、广东、广西、河北、河南、黑龙江、湖北、湖南、吉林、江苏、江西、辽宁、山东、上海、四川、天津、浙江等19个省以及辽宁省大连市历年的单产数据进行了实证研究。
(2)利用Nerlove模型以全国小麦为例进行了实证分析。说明,单产风险之外,农户对于价格波动也非常敏感,作物保险的保险标的应该对于价格风险也给予充分考虑。
(3)将VaR(风险价值)的概念引入到粮食市场价格风险的研究中来,结合ARCH类模型对其粮食市场价格的波动性进行了定量的测量,从整体上掌握了粮食价格的市场风险。
(4)构建基于Copula函数的作物收入保险定价模型。收入保险综合考虑作物单产风险与价格风险,并且不再假设两者间相互独立,而是以Copula函数为基础,建立两者的联合概率密度函数,由于分布的解析式较复杂,文中运用Monte Carlo模型实现了没有显性解情况下保险费率的计算。对作物收入保险进行定价之后,以安徽省阜阳市的具体数据为例对保险公司开办政策性作物收入保险需要收取的纯保险保费的构成比例进行了具体计算。
综上所述,本文着眼于作物产量波动风险以及农产品价格波动风险,借助于先进的金融理论创新的优势,运用有助于提高风险度量准确性以及作物保险定价的非参数核密度模型、VaR模型、GARCH-GED模型、Copula函数,改进了现有的作物产量保险定价模型,并构建了作物收入保险定价模型。实证研究的结果表明,本文构建的定价模型较原有的作物产量保险定价模型在准确刻画单产波动方面具有一定的优势,相应的研究成果可为保险公司作物保险的管理提供新的思路,有助于解决当前农户参保积极性以及参保率不高、作物保险产品比较单一等问题,从而有助于我国农业保险行业的健康、快速发展。
Crop insurance is one of the key issues concerning about'Issues of Agriculture'in China. In the process of agricultural production, farmers face various types of risks including natural risk and the risks coming from market fluctuation. Since 2004, the Chinese Government put the pilot policy-oriented agricultural insurance in practice which has facilitated the development of crop insurance program. But there are still some problems concerning China's crop insurance program, which include but not limited to just few types of insurance products and they are far less adequate to satisfying with the farmers'needs. As a result, there are only a small portion of the farmers who participated in the program etc., and yet these conditions made the insurance companies less confidence in putting effort to developing new insurance products.
This dissertation focuses on the current situation of China's policy-oriented insurance program based on the researches that have been published in and out of China by means of, improving the conventional pricing crop yield insurance model and constructing an alternative pricing model with a particular emphasis on crop revenue insurance, and following by some empirical research using the actual historical data. The research results of this article are as follows:
(1) Using the non-parametric method this article constructed a yield insurance pricing model and following by empirical study gathering crop yield data across over 19 provinces in China as well as Dalian city of Liaoning province.
(2) The Nerlove model is used utilizing the annual China wheat yield data in order to see how farmers are sensitive to the price risks besides the yield risk with the expectation that the price risk should be considered in the crop insurance product developing process.
(3) The concept of VaR (Value at Risk) is introduced in the analyzing process of food price, and the ARCH is used to model the price variance. The overall market price risk of corn and wheat can be caculated with the VaR.
(4) The revenue pricing model is constructed with the Copula method, concerning both the fluctuation of price and yield, without the assumption that the price and yield are independent with each other. With the joint density function, the Monte Carlo method is used to draw samples for the complex density analytical formula and get the premium rates of revenue insurance.
In summary, this study focuses on the fluctuation of crop yield and the risk of food price, taking advantages of sophisticated financial innovation and the actuarially risk measuring tools such as nonparametric kernel density model, VaR model, GARCH-GED model, Copula functions and so on. The pricing model of crop yield insurance is improved and the pricing model of crop revenue insurance product is developed. The empirical study results show that the newly established models in this study have some advantages than the old ones that have been put into practice over the time in China. The result of this article can be used to provide some technical support for the insurance companies as well as consultative advices of some new thinking of the program and this can bring about some reform for in the current Chinese crop insurance program. Ultimately, this will be able to make the crop insurance a healthier and faster development.
基于农业保险存在的上述问题,本文借鉴国内外现有研究成果,改进了作物产量保险定价模型,构建了作物收入保险定价模型,并在此基础上开展了实证研究。相关研究成果简述如下：
(1)构建基于非参数核密度方法的作物产量保险定价模型,克服了现有研究中假设作物单产波动服从正态分布而忽视其尖峰、厚尾、有偏性导致的问题；结合安徽、北京、福建、广东、广西、河北、河南、黑龙江、湖北、湖南、吉林、江苏、江西、辽宁、山东、上海、四川、天津、浙江等19个省以及辽宁省大连市历年的单产数据进行了实证研究。
(2)利用Nerlove模型以全国小麦为例进行了实证分析。说明,单产风险之外,农户对于价格波动也非常敏感,作物保险的保险标的应该对于价格风险也给予充分考虑。
(3)将VaR(风险价值)的概念引入到粮食市场价格风险的研究中来,结合ARCH类模型对其粮食市场价格的波动性进行了定量的测量,从整体上掌握了粮食价格的市场风险。
(4)构建基于Copula函数的作物收入保险定价模型。收入保险综合考虑作物单产风险与价格风险,并且不再假设两者间相互独立,而是以Copula函数为基础,建立两者的联合概率密度函数,由于分布的解析式较复杂,文中运用Monte Carlo模型实现了没有显性解情况下保险费率的计算。对作物收入保险进行定价之后,以安徽省阜阳市的具体数据为例对保险公司开办政策性作物收入保险需要收取的纯保险保费的构成比例进行了具体计算。
综上所述,本文着眼于作物产量波动风险以及农产品价格波动风险,借助于先进的金融理论创新的优势,运用有助于提高风险度量准确性以及作物保险定价的非参数核密度模型、VaR模型、GARCH-GED模型、Copula函数,改进了现有的作物产量保险定价模型,并构建了作物收入保险定价模型。实证研究的结果表明,本文构建的定价模型较原有的作物产量保险定价模型在准确刻画单产波动方面具有一定的优势,相应的研究成果可为保险公司作物保险的管理提供新的思路,有助于解决当前农户参保积极性以及参保率不高、作物保险产品比较单一等问题,从而有助于我国农业保险行业的健康、快速发展。
Crop insurance is one of the key issues concerning about'Issues of Agriculture'in China. In the process of agricultural production, farmers face various types of risks including natural risk and the risks coming from market fluctuation. Since 2004, the Chinese Government put the pilot policy-oriented agricultural insurance in practice which has facilitated the development of crop insurance program. But there are still some problems concerning China's crop insurance program, which include but not limited to just few types of insurance products and they are far less adequate to satisfying with the farmers'needs. As a result, there are only a small portion of the farmers who participated in the program etc., and yet these conditions made the insurance companies less confidence in putting effort to developing new insurance products.
This dissertation focuses on the current situation of China's policy-oriented insurance program based on the researches that have been published in and out of China by means of, improving the conventional pricing crop yield insurance model and constructing an alternative pricing model with a particular emphasis on crop revenue insurance, and following by some empirical research using the actual historical data. The research results of this article are as follows:
(1) Using the non-parametric method this article constructed a yield insurance pricing model and following by empirical study gathering crop yield data across over 19 provinces in China as well as Dalian city of Liaoning province.
(2) The Nerlove model is used utilizing the annual China wheat yield data in order to see how farmers are sensitive to the price risks besides the yield risk with the expectation that the price risk should be considered in the crop insurance product developing process.
(3) The concept of VaR (Value at Risk) is introduced in the analyzing process of food price, and the ARCH is used to model the price variance. The overall market price risk of corn and wheat can be caculated with the VaR.
(4) The revenue pricing model is constructed with the Copula method, concerning both the fluctuation of price and yield, without the assumption that the price and yield are independent with each other. With the joint density function, the Monte Carlo method is used to draw samples for the complex density analytical formula and get the premium rates of revenue insurance.
In summary, this study focuses on the fluctuation of crop yield and the risk of food price, taking advantages of sophisticated financial innovation and the actuarially risk measuring tools such as nonparametric kernel density model, VaR model, GARCH-GED model, Copula functions and so on. The pricing model of crop yield insurance is improved and the pricing model of crop revenue insurance product is developed. The empirical study results show that the newly established models in this study have some advantages than the old ones that have been put into practice over the time in China. The result of this article can be used to provide some technical support for the insurance companies as well as consultative advices of some new thinking of the program and this can bring about some reform for in the current Chinese crop insurance program. Ultimately, this will be able to make the crop insurance a healthier and faster development.
引文
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