An introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions
AbstractWe 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.
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Bibliographic InfoPaper provided by Xarxa de Referència en Economia Aplicada (XREAP) in its series Working Papers with number XREAP2010-03.
Length: 25 pages
Date of creation: Mar 2010
Date of revision: Mar 2010
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Postal: Espai de Recerca en Economia, Facultat de Ciències Econòmiques i Empresarials, Universitat de Barcelona, c/ Tinent Coronel Valenzuela, 1-11, 08034 Barcelona
Web page: http://www.pcb.ub.edu/xreap
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-10-30 (All new papers)
- NEP-ECM-2010-10-30 (Econometrics)
- NEP-IAS-2010-10-30 (Insurance Economics)
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