A Review of Bayesian Asymptotics in General Insurance Applications

26 Pages Posted: 3 Mar 2016 Last revised: 8 Apr 2017

See all articles by Liang Hong

Liang Hong

The University of Texas at Dallas

Ryan Martin

North Carolina State University - Department of Statistics

Date Written: July 17, 2016

Abstract

Over the last two decades, Bayesian methods have been widely used in general insurance applications, ranging from credibility theory to loss-reserves estimation, but this literature rarely addresses questions about the method's asymptotic properties. In this paper, we review the Bayesian's notion of posterior consistency in both parametric and nonparametric models and its implication on the sensitivity of the posterior to the actuary's choice of prior. We review some of the techniques for proving posterior consistency and, for illustration, we apply these results to investigate the asymptotic properties of several recently proposed Bayesian methods in general insurance.

Keywords: General insurance; nonparametric Bayes; posterior consistency; posterior robustness; property and casualty insurance

JEL Classification: C11; G22

Suggested Citation

Hong, Liang and Martin, Ryan, A Review of Bayesian Asymptotics in General Insurance Applications (July 17, 2016). Available at SSRN: https://ssrn.com/abstract=2741074 or http://dx.doi.org/10.2139/ssrn.2741074

Liang Hong (Contact Author)

The University of Texas at Dallas ( email )

2601 North Floyd Road
Richardson, TX 75083
United States

Ryan Martin

North Carolina State University - Department of Statistics ( email )

Raleigh, NC 27695-8203
United States

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