Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9552829 | Insurance: Mathematics and Economics | 2005 | 25 Pages |
Abstract
Mortality projections are major concerns for public policy, social security and private insurance. This paper implements a Bayesian log-bilinear Poisson regression model to forecast mortality. Computations are carried out using Markov Chain Monte Carlo methods in which the degree of smoothing is learnt from the data. Comparisons are made with the approach proposed by Brouhns et al. [Insur.: Math. Econ. 31 (2002) 373-393; Bull. Swiss Assoc. Actuaries (2002) 105-130], as well as with the original model of Lee and Carter [J. Am. Stat. Assoc. 87 (1992) 659-671].
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Claudia Czado, Antoine Delwarde, Michel Denuit,