Issues in Claims Reserving and Credibility: A Semiparametric Approach With Mixed Models
Katrien Antonio and
Jan Beirlant
Journal of Risk & Insurance, 2008, vol. 75, issue 3, 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.
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
https://doi.org/10.1111/j.1539-6975.2008.00278.x
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jrinsu:v:75:y:2008:i:3:p:643-676
Ordering information: This journal article can be ordered from
http://www.wiley.com/bw/subs.asp?ref=0022-4367
Access Statistics for this article
Journal of Risk & Insurance is currently edited by Joan T. Schmit
More articles in Journal of Risk & Insurance from The American Risk and Insurance Association Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().