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].
Original language | English |
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Pages (from-to) | 260-284 |
Number of pages | 25 |
Journal | Insurance: Mathematics and Economics |
Volume | 36 |
Issue number | 3 |
DOIs | |
State | Published - 24 Jun 2005 |
Keywords
- Expected remaining lifetimes
- MCMC
- Poisson regression
- Projected lifetables