Download This PaperRobust Loss Development Using MCMC
49 Pages Posted: 8 Nov 2009 Last revised: 17 Feb 2010
Date Written: February 15, 2010
Abstract
A Bayesian model of developing aggregate loss triangles in property casualty insurance is introduced. This model makes use of a heteroskedastic and skewed t-likelihood with endogenous degrees of freedom, employs model averaging by means of Reversible Jump MCMC, and accommodates a structural break in the consumption path. Further, the model is capable of incorporating expert information in the calendar year effect. The model, which has been compiled into the R package lossDev, is applied to two widely studied General Liability and Auto Bodily Injury Liability loss triangles.
Keywords: Loss development, skewed Student distribution, Reversible Jump MCMC
JEL Classification: G22
Suggested Citation: Suggested Citation
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