
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, Denuit & Vermunt (2002a,b), as well as with the original model of Lee & Carter (1992).
Item Type: | Paper |
---|---|
Keywords: | projected lifetables, expected remaining lifetimes, Poisson regression, MCMC |
Faculties: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
Subjects: | 500 Science > 510 Mathematics |
URN: | urn:nbn:de:bvb:19-epub-1768-9 |
Language: | English |
Item ID: | 1768 |
Date Deposited: | 10. Apr 2007 |
Last Modified: | 04. Nov 2020, 12:45 |