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Application of Constrained Bayes Estimation under Balanced Loss Function in Insurance Pricing
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 Title & Authors
Application of Constrained Bayes Estimation under Balanced Loss Function in Insurance Pricing
Kim, Myung Joon; Kim, Yeong-Hwa;
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 Abstract
Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and empirical Bayes estimates produce by matching first and second empirical moments; subsequently, a constrained Bayes estimate is recommended to use in case the research objective is to produce a histogram of the estimates considering the location and dispersion. The well-known squared error loss function exclusively emphasizes the precision of estimation and may lead to biased estimators. Thus, the balanced loss function is suggested to reflect both goodness of fit and precision of estimation. In insurance pricing, the accurate location estimates of risk and also dispersion estimates of each risk group should be considered under proper loss function. In this paper, by applying these two ideas, the benefit of the constrained Bayes estimates and balanced loss function will be discussed; in addition, application effectiveness will be proved through an analysis of real insurance accident data.
 Keywords
Balanced loss function;constrained Bayes estimate;insurance pricing;
 Language
English
 Cited by
1.
손해보험 위험도 추정에 대한 베이즈 위험 비교 연구,김명준;우호영;김영화;

응용통계연구, 2014. vol.27. 6, pp.1017-1028 crossref(new window)
1.
A Study on the Application of Constrained Bayes Estimation for Product Quality Control, Journal of the Korean society for quality management, 2015, 43, 1, 57  crossref(new windwow)
2.
Bayes Risk Comparison for Non-Life Insurance Risk Estimation, Korean Journal of Applied Statistics, 2014, 27, 6, 1017  crossref(new windwow)
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