我国保险业中若干问题的统计分析
发布时间：2018-08-29 14:51
【摘要】：自改革开放以来,我国的保险业一直处于高速发展状态,作为社会保障及金融体系的重要组成部分,有着不可替代的作用。但是与发达国家保险市场相比,我国的保险业还存在着许多不完善的地方,而且我国的保险业在地域发展上也存在着巨大的差距。 保险数据分析是统计学的一个重要应用领域,从前期的保费核定工作开始,再经过一系列风险评估、赔付率计算,到后期的保费收入、报案量、结案量预测,统计理论贯穿始终。随着保险业规模的不断扩大,各保险公司数据激增,亦趋于多元化,致使分析难度加大。运用合理的统计理论和方法对保险业中的相关数据进行统计分析,探索保险业的发展规律,对指导我国保险业的健康发展具有重要意义。 本文运用统计学的理论和方法,针对我国保险业中的两个具体问题进行了探索研究。具体来说,一方面,我们研究了我国保险市场在地域上的一种宏观不平衡发展状况,采用保费收入、保险密度、保险深度三个指标,用聚类方法分析了我国31个省(市)保险市场的发展情况,得出在东、西、中部地区,保险市场、保险需求差距颇大,发展很不均衡。另一方面,我们从微观问题入手,以中国平安河南省分公司近几年来车险的实际数据为例,采用时间序列方法,研究了保险公司的报案量、结案量、保费收入等指标之间的关系以及相应的建模与预测问题。由于该数据具有季节趋势,本文首先通过季节指数方法,对各个指标消除季节趋势,再做出拟合、预测。另外,考虑到报案量与结案量可能会有一定的相关性,本文再次通过协整分析、脉冲响应函数进一步对数据做出分析,证明上一期的结案量对当期报案量具有促进作用。
[Abstract]:Since the reform and opening up, China's insurance industry has been in a state of rapid development, as an important part of social security and financial system, has an irreplaceable role. But compared with the developed countries'insurance market, China's insurance industry still has many imperfections, and China's insurance industry also exists in the regional development. There is a huge gap.
Insurance data analysis is an important application field of statistics. From the early stage of premium verification work, and then through a series of risk assessment, compensation rate calculation, to the late stage of premium income, the number of cases reported, the number of cases forecast, statistical theory runs through all the time. The application of reasonable statistical theory and methods to the statistical analysis of the relevant data in the insurance industry and the exploration of the law of the development of the insurance industry are of great significance to the healthy development of China's insurance industry.
In this paper, two specific problems in China's insurance industry are explored and studied by using the theory and method of statistics. Specifically, on the one hand, we have studied a kind of macro-unbalanced development of China's insurance market in the region, using three indicators of premium income, insurance density and insurance depth, and using clustering method to analyze China's insurance industry. The development of insurance market in 31 provinces (cities) shows that there is a big gap between insurance market and insurance demand in eastern, western and central regions, and the development is very uneven. On the other hand, we start with micro-problems and take the actual data of car insurance in recent years of Ping'an Henan Branch of China as an example to study the reports of insurance companies by using time series method. Because of the seasonal trend of the data, this paper firstly eliminates the seasonal trend of each index through the seasonal index method, and then makes a fitting and prediction. In addition, considering that the number of reported cases and the number of closed cases may have a certain correlation, this paper again communicates. Over-cointegration analysis and impulse response function further analyzed the data, proving that the number of cases closed in the previous period has a positive effect on the number of cases reported in the current period.
【学位授予单位】：华中师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F842.4;F224
本文编号：2211542
[Abstract]:Since the reform and opening up, China's insurance industry has been in a state of rapid development, as an important part of social security and financial system, has an irreplaceable role. But compared with the developed countries'insurance market, China's insurance industry still has many imperfections, and China's insurance industry also exists in the regional development. There is a huge gap.
Insurance data analysis is an important application field of statistics. From the early stage of premium verification work, and then through a series of risk assessment, compensation rate calculation, to the late stage of premium income, the number of cases reported, the number of cases forecast, statistical theory runs through all the time. The application of reasonable statistical theory and methods to the statistical analysis of the relevant data in the insurance industry and the exploration of the law of the development of the insurance industry are of great significance to the healthy development of China's insurance industry.
In this paper, two specific problems in China's insurance industry are explored and studied by using the theory and method of statistics. Specifically, on the one hand, we have studied a kind of macro-unbalanced development of China's insurance market in the region, using three indicators of premium income, insurance density and insurance depth, and using clustering method to analyze China's insurance industry. The development of insurance market in 31 provinces (cities) shows that there is a big gap between insurance market and insurance demand in eastern, western and central regions, and the development is very uneven. On the other hand, we start with micro-problems and take the actual data of car insurance in recent years of Ping'an Henan Branch of China as an example to study the reports of insurance companies by using time series method. Because of the seasonal trend of the data, this paper firstly eliminates the seasonal trend of each index through the seasonal index method, and then makes a fitting and prediction. In addition, considering that the number of reported cases and the number of closed cases may have a certain correlation, this paper again communicates. Over-cointegration analysis and impulse response function further analyzed the data, proving that the number of cases closed in the previous period has a positive effect on the number of cases reported in the current period.
【学位授予单位】：华中师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F842.4;F224
【参考文献】
相关期刊论文 前8条
1 李永猛;;货币政策对我国城乡居民消费差距的脉冲响应分析[J];研究生法学;2011年04期
2 郑伟;刘永东;;中国保险业区域发展比较研究——基于“保险基准深度比”的分析[J];经济科学;2008年05期
3 张云;高垒;;基于乘积季节模型的我国保费收入的预测研究[J];金融经济;2009年14期
4 张芳洁;影响我国保险业发展的经济因素的实证分析[J];数量经济技术经济研究;2004年03期
5 陈权宝,聂锐;我国保险费收入预测模型的选择[J];统计与决策;2005年17期
6 梁来存;皮友静;;我国保费收入的ARIMA模型与预测[J];统计与决策;2006年07期
7 赵长利;陈海泳;陈德阳;;中国保险业保费收入灰色预测模型的研究[J];统计与决策;2007年13期
8 曹明;;我国能源强度与能源价格之间的脉冲响应分析[J];统计与决策;2011年03期
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