我国粮食单产保险纯费率厘定的实证研究

粮食保险属于政策性农业保险,其费率厘定应以风险区划为基础,准确的费率厘定将有助于政府制订出科学的保险支农政策。本文从以产量变化测度自然风险对粮食安全的影响这一新的视角建立了粮食安全自然风险影响的评价指标体系。利用系统聚类法、K-均值聚类法和模糊聚类法对我国粮食生产进行了省级保险风险区划,并以Fisher判别法、Bayes判别法和逐步判别法进行了回判验证。在对各省（市、区）粮食单产分布进行检验的基础上,选取经验费率法厘定了单产保险的纯费率,并结合风险区划结果和政策取向对纯费率进行了调整。进一步的研究需要实施较小基本单位的风险区划和费率厘定,基本单位越小,费率厘定越符合实际,但工作量越大。     

农作物产量保险区域化差别费率厘定的可行性——基于非参数核密度估计实证

采用非参数核函数平滑法以辽宁省、黑龙江省以及大连市的水稻、玉米和大豆三种农作物历年单位面积产量为例拟合了单产损失分布,同时利用传统的正态概率密度对区域作物单产分布进行了拟合。在拟合损失分布的基础上,分别厘定出不同保险水平农作物区域产量保险的纯保险费率。经测算发现,传统的正态概率密度下厘定的纯保险费率均低于非参数核密度下测算的纯费率,正态法低估了农作物单产的风险。保险水平在70%⁸0%间的参数法及非参数法测算的纯保险费率均低于政策性农业保险的现行费率。另外,在数据可得的基础上,还应该确定适当的厘定保费费率的区域以充分识别风险,更精确的计算保费。     

基于混合Copula模型的水稻保险费率厘定

模拟产量风险和价格风险的联合分布是农业收入保险费率厘定的重点和难点。借助核密度估计方法和混合Copula模型研究了水稻产量和价格风险因子的联合分布并厘定了产量、价格和收入三种保险的纯费率。研究表明:(1)与单一Copula函数相比,混合Copula模型更适合拟合多风险因子的联合分布。(2)早稻价格风险导致的收入损失高于产量风险导致的收入损失,中稻和晚稻产量风险导致的收入损失高于价格风险导致的收入损失。(3)由于产量风险和价格风险的对冲,江苏、安徽、江西、河南、贵州和广西具备了在中稻、晚稻主产区试点收入保险的客观条件。(4)在100%的保障水平下,中国水稻产区早稻收入险纯费率为8.60%～12.84%、中稻收入险纯费率为5.89%～12.07%、晚稻收入险纯费率为4.59%～7.94%。     

保险监管对巨灾风险债券供给的影响途径及计量模型

在巨灾风险债券供给方面,保险监管者比金融监管者起了更大的作用。文章首先讨论了保险监管影响巨灾风险债券供给的四个途径;其次通过建立最低偿付能力监管下的巨灾风险债券供给模型,分析了一个和常识不符的结论:本金和利息保证比率的提高不会减少巨灾风险债券的供给;此外费率监管下的数学模型显示,在巨灾风险债券的影响下,巨灾保险费率可以趋于稳定。     

模糊风险下的ASF模型和中国巨灾保险实证研究

为了解释保险公司对巨灾风险的普遍厌恶,并探讨巨灾的承保条件,文章在模糊风险假设下建立了ASF模型,给出了巨灾保险中资本金、保单数量、损失金额、概率及相关系数等关键因子的理论分析;实证研究了中国地震数据,探讨了符合经验的费率水平和损失边界,这从某种程度上解释了巨灾保险供给不足的现象,提出了一种评估承保风险的办法。研究结果显示,地震并非不可保风险。文章还从保险公司和国家层面针对如何承保巨灾提出了相关的政策建议。     

气温天气指数保险的费率厘定——以粮食作物为例

天气指数保险是传统农业保险、区域产量保险的创新。选择天气指数保险,探讨其费率厘定,有助于克服道德风险和逆选择,确保农业保险快速、健康地发展。粮食作物气温天气指数保险的费率厘定,首先要测算低温(或高温)的严重程度,计算低温(或高温)测度值;再分析气候因素导致粮食作物减产的程度,计算气候减产率;然后利用计量经济分析方法,确立气候减产率与低温(或高温)测度值之间的定量关系;最后根据该定量关系以及低温(或高温)测度值的期望值,求得气温天气指数保险的费率。该费率厘定方法,科学地测定了低温(或高温)程度,把赔付概率、触发值、费率厘定有机地联系在一起。并以长沙县早稻保险为例进行了实证研究。     

基于累积索赔金额的最优奖惩系统

商业汽车保险的费率可以分解为先验费率和后验费率.先验费率是基于被保险车辆的先验风险特征信息(如驾驶人的性别和年龄、车辆使用性质)应用广义线性模型厘定的费率,而后验费率是基于被保险车辆的索赔经验(如索赔次数)应用奖惩系统对先验费率进行调整而得到的费率.厘定先验费率常用的广义线性模型包括索赔频率模型、索赔强度模型和累积索赔金额模型.实际应用中的奖惩系统通常基于被保险车辆的经验索赔次数对先验费率进行调整,没有考虑索赔金额的影响,也没有考虑先验信息的影响,有可能造成重复性的奖励或惩罚.累积索赔金额是被保险车辆在保险期间的索赔金额之和,既包含索赔次数信息,也包含索赔金额信息,可以更加准确地揭示被保险车辆的索赔经验信息.本文应用被保险车辆多年期的纵向累积索赔金额数据建立了一种新的奖惩系统,应用零调整逆高斯回归模型厘定先验费率,并在线性约束下用极大似然法同时估计先验费率因子和奖惩系数,避免了传统奖惩系统对被保险人可能造成的重复性奖励或惩罚,有效改进了后验费率的厘定结果.     

不同产量分布下湖北省县级水稻产量保险的纯费率厘定

文章利用湖北省82个县市1991～2007年的水稻产量,使用极大似然法估计Normal、LogNormal、Logistic、Beta、Weibull分布,并以2001～2007的平均产量为关键产量,以拟合的分布为水稻单产分布,厘定了湖北省县级水稻产量保险的纯费率.研究表明:大部分县市在Logistic、Weibull分布下拟合得比较好,有68个县市在这两个分布下的A-D检验值最小;非对称分布下的纯费率一般要高于对称分布下的纯费率;纯费率的精确厘定依赖于单产分布的正确选择;最佳分布下的纯费率能够很好地反映整个经验期的产量波动.     

健康保险与财产保险的定价比较

面对日益开放的团险和健康险市场,不仅要从经营风险,筹资渠道等方面加强管理,还要从技术层面上寻求健康保险市场的长期发展.健康保险以发病率为依据而非以死亡率为依据,风险控制难度大,专业技术要求高,因此与人寿保险在定价上有不同之处,其费率厘定的原理与财产保险相似.本文对健康保险与财产保险的费率厘定方法进行比较分析.     

农业指数保险定价模型的研究进展及改进策略

农业指数保险是一种新型的农业保险产品,在农业风险管理中具有独特的优势和应用价值,但同时也在风险建模和费率厘定中面临着一系列挑战,近年来受到业界和学界的广泛关注。区域产量保险和天气指数保险是目前应用最为广泛的两种农业指数保险,它们在风险定价中面临的挑战主要包括经验数据不足、不同风险之间相依关系复杂、普遍存在基差风险等。通过对区域产量风险建模、天气指数构造及其分布拟合、农业相依风险建模、基差风险度量和控制等方面对相关研究成果的系统梳理和评述,指出了现有定价模型存在的不足和未来研究需要重点关注的问题,对于进一步完善农业指数保险的风险建模方法,提高农业指数保险定价结果的合理性和准确性具有重要现实意义。     

Ruin problem of a two-dimensional fractional Brownian motion risk process

This paper investigates ruin probability and ruin time of a two-dimensional fractional Brownian motion risk process. The net loss process of an insurance company is modeled by a fractional Brownian motion. The two-dimensional fractional Brownian motion risk process models the surplus processes of an insurance and a reinsurance company, where the net loss is divided between them in some specified proportions. The ruin problem considered is that of the two-dimensional risk process first entering the negative quadrant, that is, the simultaneous ruin problem. We derive both asymptotics of the ruin probability and approximations of the scaled conditional ruin time as the initial capital tends to infinity.     

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.     

Multistate models in health insurance

We illustrate how multistate Markov and semi-Markov models can be used for the actuarial modeling of health insurance policies, focusing on health insurances that are pursued on a similar technical basis to that of life insurance. In the first part, we give an overview of the basic modeling frameworks that are commonly used and explain the calculation of prospective reserves and net premiums. In the second part, we discuss the biometric insurance risk, focusing on the calculation of implicit safety margins. We present new results on implicit margins in the semi-Markov model and on biometric estimation risk in the Markov model, and we explain why there is a need for future research concerning the systematic biometric risk.     

Estimate for the Finite-time Ruin Probability in the Discrete-time Risk Model with Insurance and Financial Risks

In this article, we consider a discrete-time risk model with insurance and financial risks. We derive some refinements of a general asymptotic formula for the finite-time ruin probability under the assumptions that the net losses follow a common distribution in the intersection between the subexponential class and the Gumbel maximum domain of attraction, and the stochastic discount factors of the risky asset have a common distribution with extended regular variation. The obtained asymptotic upper and lower bounds are transparent and computable.     

The case for small area microdata

Summary.  Census data are available in aggregate form for local areas and, through the samples of anonymized records (SARs), as samples of microdata for households and individuals. In 1991 there were two SAR files: a household file and an individual file. These have a high degree of detail on the census variables but little geographical detail, a situation that will be exacerbated for the 2001 SAR owing to the loss of district level geography on the individual SAR. The paper puts forward the case for an additional sample of microdata, also drawn from the census, that has much greater geographical detail. Small area microdata (SAM) are individual level records with local area identifiers and, to maintain confidentiality, reduced detail on the census variables. Population data from seven local authorities, including rural and urban areas, are used to define prototype samples of SAM. The rationale for SAM is given, with examples that demonstrate the role of local area information in the analysis of census data. Since there is a trade-off between the extent of local detail and the extent of detail on variables that can be made available, the confidentiality risk of SAM is assessed empirically. An indicative specification of the SAM is given, having taken into account the results of the confidentiality analysis.     

基于分层广义线性模型的非寿险费率厘定精算模型研究

非寿险业务中的损失数据结构日益复杂,呈现异质性与相关性并存的异象。分层广义线性模型能够突破传统费率厘定精算方法仅分析风险个体同一保单年损失数据的局限,可以提高复杂结构损失数据预测的准确性。基于分层广义线性模型等方法,研究具有多年损失数据的非寿险费率厘定问题,并以车险和工伤补偿保险的两组损失数据为例进行实证分析。研究结果表明,相对于GLM而言,考虑随机效应后GLMM的拟合优度大幅改善,GLMM与HGLM可以更有效地反映不同风险个体的差异,并有利于揭示风险个体在多个保险期内损失的异质性与相关性。     

引入所得税的Merton模型存款保险定价研究

存款保险定价是存款保险制度建设中的核心内容,合理的保费厘定关乎存款保险制度的建立和存款机构的参与程度。从传统的Merton模型入手,在模型中引入了存款机构和保险公司所得税因素,将税盾效应应用于存款保险的定价中,建立了拓展的Merton模型。选取国内10家上市银行为样本,测算存款保险的保费费率,通过费率间的比较分析,得出引入所得税的拓展的存款保险定价模型能够明显降低保费费率,税盾效应显著。从风险测算和分阶段建立存款保险制度两个方面提出相关建议。