We formulate, study and calibrate a continuous-time model for the joint evolution of the mortality surface of multiple populations. We model the mortality intensity by age and population as a mixture of stochastic latent factors, that can be either population-specific or common to all populations. These factors are described by affine time-(in)homogeneous stochastic processes. Traditional, deterministic mortality laws can be extended to multi-population stochastic counterparts within our framework. We detail the calibration procedure when factors are Gaussian, using centralized data-fusion Kalman filter. We provide an application based on the joint mortality of UK and Dutch males and females. Although parsimonious, the specification we calibrate provides a good fit of the observed mortality surface (ages 0–89) of both sexes and populations between 1960 and 2013.
Jevtic, P., Regis, L. (2019). A continuous-time stochastic model for the mortality surface of multiple populations. INSURANCE MATHEMATICS & ECONOMICS, 88, 181-195 [10.1016/j.insmatheco.2019.07.001].
A continuous-time stochastic model for the mortality surface of multiple populations
Regis L.
2019-01-01
Abstract
We formulate, study and calibrate a continuous-time model for the joint evolution of the mortality surface of multiple populations. We model the mortality intensity by age and population as a mixture of stochastic latent factors, that can be either population-specific or common to all populations. These factors are described by affine time-(in)homogeneous stochastic processes. Traditional, deterministic mortality laws can be extended to multi-population stochastic counterparts within our framework. We detail the calibration procedure when factors are Gaussian, using centralized data-fusion Kalman filter. We provide an application based on the joint mortality of UK and Dutch males and females. Although parsimonious, the specification we calibrate provides a good fit of the observed mortality surface (ages 0–89) of both sexes and populations between 1960 and 2013.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1088234