Constrained Bayes and Empirical Bayes Estimator Applications in Insurance Pricing

Title & Authors
Constrained Bayes and Empirical Bayes Estimator Applications in Insurance Pricing
Kim, Myung Joon; Kim, Yeong-Hwa;

Abstract
Bayesian and empirical Bayesian methods have become quite popular in the theory and practice of statistics. However, the objective is to often produce an ensemble of parameter estimates as well as to produce the histogram of the estimates. For example, in insurance pricing, the accurate point estimates of risk for each group is necessary and also proper dispersion estimation should be considered. Well-known Bayes estimates (which is the posterior means under quadratic loss) are underdispersed as an estimate of the histogram of parameters. The adjustment of Bayes estimates to correct this problem is known as constrained Bayes estimators, which are matching the first two empirical moments. In this paper, we propose a way to apply the constrained Bayes estimators in insurance pricing, which is required to estimate accurately both location and dispersion. Also, the benefit of the constrained Bayes estimates will be discussed by analyzing real insurance accident data.
Keywords
Bayes estimate;constrained Bayes estimate;insurance pricing;
Language
English
Cited by
1.
Application of Constrained Bayes Estimation under Balanced Loss Function in Insurance Pricing,;;

Communications for Statistical Applications and Methods, 2014. vol.21. 3, pp.235-243
2.
손해보험 위험도 추정에 대한 베이즈 위험 비교 연구,김명준;우호영;김영화;

응용통계연구, 2014. vol.27. 6, pp.1017-1028
1.
Bayes Risk Comparison for Non-Life Insurance Risk Estimation, Korean Journal of Applied Statistics, 2014, 27, 6, 1017
2.
Application of Constrained Bayes Estimation under Balanced Loss Function in Insurance Pricing, Communications for Statistical Applications and Methods, 2014, 21, 3, 235
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