City Research Online

Abstract

The problem of modelling the joint distribution of survival times in a competing risks model, using copula functions is considered. In order to evaluate this joint distribution and the related overall survival function, a system of non-linear differential equations is solved, which relates the crude and net survival functions of the modelled competing risks, through the copula. A similar approach to modelling dependent multiple decrements was applied by Carriere (1994) who used a Gaussian copula applied to an incomplete double decrement model which makes it difficult to calculate any actuarial functions and draw relevant conclusions. Here, we extend this methodology by studying the effect of complete and partial elimination of up to four competing risks on the overall survival function, the life expectancy and life annuity values. We further investigate how different choices of the copula function affect the resulting joint distribution of survival times and in particular the actuarial functions which are of importance in pricing life insurance and annuity products. For illustrative purposes, we have used a real data set and used extrapolation to prepare a complete multiple decrement model up to age 120. Extensive numerical results illustrate the sensitivity of the model with respect to the choice of copula and its parameter(s).

Publication Type:	Article
Additional Information:	NOTICE: this is the author’s version of a work that was accepted for publication in Insurance: Mathematics and Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Insurance: Mathematics and Economics, Volume 41, Issue 3, November 2007, Pages 339–361, http://dx.doi.org/10.1016/j.insmatheco.2006.11.006
Publisher Keywords:	dependent competing risk model, disease elimination, failure times, overall survival function, copulas, spline function
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School > Finance
Related URLs:	Author
SWORD Depositor:	Symplectic Administrator

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