Modelling repeated insurance claim frequency data using the generalized linear mixed model
AbstractMost of the methods used to estimate claim frequency rates in general insurance have assumed that data are independent. However, it is not uncommon for information stored in the database of an insurance company to contain previous years' claim data from each policyholder. We consider the application of the generalized linear mixed model approach to the analysis of repeated insurance claim frequency data in which a conditionally fixed random effect vector is incorporated explicitly into the linear predictor to model the inherent correlation. A motor insurance data set is used as the basis for simulation to demonstrate the advantages of the method. Ignoring the underlying association for observations within the same policyholder results in an underestimation of the standard error of the parameter estimates and a remarkable reduction in the prediction accuracy. The method provides a viable alternative for incorporating repeated claim experience that enables the revision of rates in general insurance.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Journal of Applied Statistics.
Volume (Year): 30 (2003)
Issue (Month): 8 ()
Contact details of provider:
Web page: http://www.tandfonline.com/CJAS20
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kelvin K. W. Yau & Anthony Y. C. Kuk, 2002. "Robust estimation in generalized linear mixed models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(1), pages 101-117.
- Dionne, G. & Vanasse, C., 1988.
"A Generalization of Automobile Insurance Rating Models: the Negative Binomial Distribution with a Regression Component,"
Cahiers de recherche
8833, Universite de Montreal, Departement de sciences economiques.
- Dionne, G. & Vanasse, C., 1988. "A Generalization Of Automobile Insurance Rating Models: The Negative Binomial Distribution With A Regression Component," Cahiers de recherche 8833, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- K. K. W. Yau, 1999. "Estimation of surgeon effects in the analysis of post-operative colorectal cancer patients data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(2), pages 257-272.
- Stroinski, Krzysztof J. & Currie, Iain D., 1989. "Selection of variables for automobile insurance rating," Insurance: Mathematics and Economics, Elsevier, vol. 8(1), pages 35-46, March.
- GÓMEZ GARCÍA, J.Mª & PELÁEZ FERMOSO, F.J. & y GARCÍA GONZÁLEZ, A., 2005. "Repercusiones del envejecimiento demográfico sobre el sistema público de pensiones en Castilla y León," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 23, pages 235-253, Abril.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.