A Bayesian smoothing spline method for mortality modelling
Arto Luoma,
Anne Puustelli and
Lasse Koskinen
Annals of Actuarial Science, 2012, vol. 6, issue 2, 284-306
Abstract:
We propose a new method for two-dimensional mortality modelling. Our approach smoothes the data set in the dimensions of cohort and age using Bayesian smoothing splines. The method allows the data set to be imbalanced, since more recent cohorts have fewer observations. We suggest an initial model for observed death rates, and an improved model which deals with the numbers of deaths directly. Unobserved death rates are estimated by smoothing the data with a suitable prior distribution. To assess the fit and plausibility of our models we perform model checks by introducing appropriate test quantities. We show that our final model fulfils nearly all requirements set for a good mortality model.
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:cup:anacsi:v:6:y:2012:i:02:p:284-306_00
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