Cohort Effects in Mortality Modelling: A Bayesian State-Space Approach

44 Pages Posted: 31 Jan 2017 Last revised: 22 Oct 2019

See all articles by Simon Man Chung Fung

Simon Man Chung Fung

Commonwealth Bank of Australia

Gareth Peters

University of California Santa Barbara; University of California, Santa Barbara

Pavel V. Shevchenko

Macquarie University - Department of Actuarial Studies and Business Analytics

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Date Written: March 30, 2018

Abstract

Cohort effects are important factors in determining the evolution of human mortality for certain countries. Extensions of dynamic mortality models with cohort features have been proposed in the literature to account for these factors under the generalised linear modelling framework. In this paper we approach the problem of mortality modelling with cohort factors incorporated through a novel formulation under a state-space methodology. In the process we demonstrate that cohort factors can be formulated naturally under the state-space framework, despite the fact that cohort factors are indexed according to year-of-birth rather than year. Bayesian inference for cohort models in a state-space formulation is then developed based on an efficient Markov chain Monte Carlo sampler, allowing for the quantification of parameter uncertainty in cohort models and resulting mortality forecasts that are used for life expectancy and life table constructions. The effectiveness of our approach is examined through comprehensive empirical studies involving male and female populations from various countries. Our results show that cohort patterns are present for certain countries that we studied and the inclusion of cohort factors are crucial in capturing these phenomena, thus highlighting the benefits of introducing cohort models in the state-space framework. Forecasting of cohort models is also discussed in light of the projection of cohort factors.

Keywords: mortality modelling, cohort features, state-space models, Bayesian inference, Markov chain Monte Carlo

JEL Classification: C11, C13, C15, C53, J11

Suggested Citation

Fung, Man Chung and Peters, Gareth and Shevchenko, Pavel V., Cohort Effects in Mortality Modelling: A Bayesian State-Space Approach (March 30, 2018). Available at SSRN: https://ssrn.com/abstract=2907868 or http://dx.doi.org/10.2139/ssrn.2907868

Man Chung Fung (Contact Author)

Commonwealth Bank of Australia

CBP
Sydney, NSW 2064
Australia

Gareth Peters

University of California Santa Barbara ( email )

Santa Barbara, CA 93106
United States

University of California, Santa Barbara ( email )

Pavel V. Shevchenko

Macquarie University - Department of Actuarial Studies and Business Analytics ( email )

Australia

HOME PAGE: http://www.mq.edu.au/research/centre-for-risk-analytics/pavel-shevchenko

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