Bayesian Poisson Log-Bilinear Mortality Projections

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).