Title: Issues in claims reserving and credibility: a semiparametric approach with mixed models
Authors: Antonio, Katrien ×
Beirlant, Jan #
Issue Date: Aug-2008
Publisher: American Risk and Insurance Association, Inc.
Series Title: The Journal of Risk and Insurance vol:75 issue:3 pages:643-676
Abstract: Using the statistical methodology of semi-parametric regression and its connection with mixed models, this article revisits smoothing models for loss reserving and credibility. Apart from the flexibility inherent to all semiparametric methods, advantages of the semiparametric approach developed here are threefold. First, a Bayesian implementation of these smoothing models is relatively straightforward and allows simulation from the full predictive distribution of quantities of interest. Second, because the constructed models have an interpretation as (generalized) linear mixed models ((G)LMMs), standard statistical theory and software for (G)LMMs can be used. Third, more complicated data sets, dealing, for example, with quarterly development in a reserving context, heavy tails, semi-continuous data, or extensive longitudinal data, can be modeled within this framework.
ISSN: 0022-4367
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center Insurance, Leuven
Statistics Section
× corresponding author
# (joint) last author

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