Multi-Population Mortality Modelling: A Bayesian Approach

36 Pages Posted: 4 Jun 2022

See all articles by Dan Zhu

Dan Zhu

Monash University - Department of Econometrics & Business Statistics

Jianjie Shi

Monash University

Yanlin Shi

Macquarie University, Macquarie Business School

PENGJIE WANG

Monash University

Abstract

Modelling mortality co-movements for multiple populations has significant implications for mortality/longevity risk management. This paper considers a population composed of heterogeneous sub-populations that 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 to fit the co-movements over time. An efficient Bayesian Markov Chain Monte-Carlo method is developed to estimate the unknown parameters to address the computational complexity. Our empirical application to the mortality data collected for the Group of Seven (G7) nations demonstrates the efficacy of our approach.

Keywords: Lee-Carter Model, Multi-population Approach, Markov Chain Monte Carlo, Vector Error

Suggested Citation

Zhu, Dan and Shi, Jianjie and Shi, Yanlin and WANG, PENGJIE, Multi-Population Mortality Modelling: A Bayesian Approach. Available at SSRN: https://ssrn.com/abstract=4127901 or http://dx.doi.org/10.2139/ssrn.4127901

Dan Zhu (Contact Author)

Monash University - Department of Econometrics & Business Statistics ( email )

Wellington Road
Clayton, Victoria 3168
Australia

Jianjie Shi

Monash University ( email )

Yanlin Shi

Macquarie University, Macquarie Business School ( email )

New South Wales 2109
Australia

PENGJIE WANG

Monash University ( email )

23 Innovation Walk
Wellington Road
Clayton, Victoria 3800
Australia

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