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An Application Of Generalized Linear Models On Inherent Defect Insurance Pricing

Posted on:2012-04-22Degree:MasterType:Thesis
Country:ChinaCandidate:J J LiangFull Text:PDF
GTID:2212330368488000Subject:Civil Engineering Management
Abstract/Summary:PDF Full Text Request
Given our construction quality guarantee system can not meet the development needs and yield a series of questions, so China's Ministry of Construction introduces construction quality insurance system, which was tried in 14 cities from 2006. But the results are not satisfactory, there are many reasons for such results, and the unreasonable rate is one of them.Construction quality insurance is a new kind of insurance for our country. The rate making is lack of reasonable and scientific. Hope that through this study, this paper will give a rational and scientific method to determine the premium rate and to reduce the premium rate determined by randomness and uncertainty.This paper analyzes China's construction quality guarantee system and introduces the origin and the concept of construction quality insurance, and the development in our country. And then the article applies qualitative analysis to analyze the factors which affect the construction quality. Considered the selection criteria of the classification variable of premium rate, the paper establishes the classification variable system of the construction quality insurance premium rate. After that, this article recommends the methods of classification ratemaking and focuses on the introduction of the Generalized Linear Models, including its assumptions, the general form, parameter estimation and the advantages and disadvantages. On this basis, this paper establishes models of construction quality insurance ratemaking. At last, a simple simulation example has demonstrated how the model works and proved its feasibility. The model provides a feasible idea to solve the problem of determined the premium rate of construction quality insurance.
Keywords/Search Tags:Inherent Defect Insurance, Rate Making, Generalized Linear Models
PDF Full Text Request
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