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).