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- Title
Multi-population mortality modelling: a Bayesian hierarchical approach.
- Authors
Shi, Jianjie; Shi, Yanlin; Wang, Pengjie; Zhu, Dan
- Abstract
Modelling mortality co-movements for multiple populations has significant implications for mortality/longevity risk management. This paper assumes that multiple populations are heterogeneous sub-populations randomly drawn from a hypothetical super-population. Those heterogeneous sub-populations may exhibit various patterns of mortality dynamics across different age groups. We propose a hierarchical structure of these age patterns to ensure the model stability and use a Vector Error Correction Model (VECM) to fit the co-movements over time. Especially, a structural analysis based on the VECM is implemented to investigate potential interdependence among mortality dynamics of the examined populations. An efficient Bayesian Markov Chain Monte-Carlo method is also developed to estimate the unknown parameters to address the computational complexity. Our empirical application to the mortality data collected for the Group of Seven nations demonstrates the efficacy of our approach.
- Subjects
GROUP of Seven countries; MARKOV chain Monte Carlo; AGE groups; MARKOV processes
- Publication
Astin Bulletin, 2024, Vol 54, Issue 1, p46
- ISSN
0515-0361
- Publication type
Article
- DOI
10.1017/asb.2023.29