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.
Original language | English (US) |
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Pages (from-to) | 181-195 |
Number of pages | 15 |
Journal | Insurance: Mathematics and Economics |
Volume | 88 |
DOIs | |
State | Published - Sep 2019 |
Keywords
- Centralized data fusion
- Continuous-time stochastic mortality
- Kalman filter estimation
- Mortality surface
- Multi-population mortality
ASJC Scopus subject areas
- Statistics and Probability
- Economics and Econometrics
- Statistics, Probability and Uncertainty