An Introduction to Parametric and Non-Parametric Models for Bivariate Positive Insurance Claim Severity Distributions

XREAP 2010-03

25 Pages Posted: 22 Apr 2011

See all articles by David Pitt

David Pitt

University of Melbourne - Department of Economics

Montserrat Guillen

Date Written: February 28, 2010

Abstract

We present a real data set of claims amounts where costs related to damage are recorded separately from those related to medical expenses. Only claims with positive costs are considered here. Two approaches to density estimation are presented: a classical parametric and a semi-parametric method, based on transformation kernel density estimation. We explore the data set with standard univariate methods. We also propose ways to select the bandwidth and transformation parameters in the univariate case based on Bayesian methods. We indicate how to compare the results of alternative methods both looking at the shape of the overall density domain and exploring the density estimates in the right tail.

Suggested Citation

Pitt, David and Guillen, Montserrat, An Introduction to Parametric and Non-Parametric Models for Bivariate Positive Insurance Claim Severity Distributions (February 28, 2010). XREAP 2010-03. Available at SSRN: https://ssrn.com/abstract=1815127 or http://dx.doi.org/10.2139/ssrn.1815127

David Pitt (Contact Author)

University of Melbourne - Department of Economics ( email )

Melbourne, 3010
Australia

No contact information is available for Montserrat Guillen

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