2020/10/09 by Zhen Liu, Xiaoqian Sun, Liu, Zhen +5
Decision Sciences · Health Professions · Social Sciences · #Applications (stat.AP) #FOS: Computer and information sciences #Global Health Care Issues #Insurance, Mortality, Demography, Risk Management #demographic modeling and climate adaptation
paper · pdf · doi:10.48550/arxiv.2010.04775
openalex publication_date 2020/10/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The improvement of mortality projection is a pivotal topic in the diverse branches related to insurance, demography, and public policy. Motivated by the thread of Lee-Carter related models, we propose a Bayesian model to estimate and predict mortality rates for multi-population. This new model features in information borrowing among populations and properly reflecting variations of data. It also provides a solution to a long-time overlooked problem: model selection for dependence structures of population-specific time parameters. By introducing a Dirac spike function, simultaneous model selection and estimation for population-specific time effects can be achieved without much extra computation cost. We use the Japanese mortality data from Human Mortality Database to illustrate the desirable properties of our model.