JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Constrained Bayes and Empirical Bayes Estimator Applications in Insurance Pricing
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Constrained Bayes and Empirical Bayes Estimator Applications in Insurance Pricing
Kim, Myung Joon; Kim, Yeong-Hwa;
  PDF(new window)
 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 crossref(new window)
2.
손해보험 위험도 추정에 대한 베이즈 위험 비교 연구,김명준;우호영;김영화;

응용통계연구, 2014. vol.27. 6, pp.1017-1028 crossref(new window)
1.
Application of Constrained Bayes Estimation under Balanced Loss Function in Insurance Pricing, Communications for Statistical Applications and Methods, 2014, 21, 3, 235  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)
 References
1.
Louis, T. A. (1984). Estimating a population of parameter values using Bayes and empirical Bayes method, Journal of the American Statistical Association, 79, 393-398. crossref(new window)

2.
Ghosh, M. (1992). Constrained Bayes estimation with applications, Journal of the American Statistical Association, 87, 533-540. crossref(new window)

3.
Ghosh, M. and Kim, D. (2002). Multivariate constrained Bayes estimation, Pakistan Journal of Statistics, 18, 143-148.

4.
Ghosh, M., Kim, M. and Kim, D. (2008). Constrained Bayes and empirical Bayes estimation under random effects normal ANOVA model with balanced loss function, Journal of Statistical Planning and Inference, 138, 2017-2028. crossref(new window)

5.
Zellner, A. (1988). Bayesian analysis in econometrics, Journal of Econometrics, 37, 27-50. crossref(new window)

6.
Zellner, A. (1992). Bayesian and non-Bayesian estimation using balanced loss functions, Statistical Decision Theory and Related Topics V, Springer-Verlag, New York, 377-390.