Bo Wang (University of Leicester) – Multipopulation mortality modelling and forecasting: a multivariate functional principal component approach

Human mortality patterns and trajectories in closely related populations are likely linked together and share similarities. It is always desirable to model them simultaneously while taking their heterogeneity into account. When a mortality model is applied to each population separately, they tend to result in divergent forecasts of life expectancy in the long term. We introduce a method for joint and coherent mortality modelling and forecasting of multiple subpopulations using the multivariate functional principal component analysis techniques, which ensures the non-divergent forecasting in the long run when several subpopulation groups have similar socio-economic conditions or common biological characteristics. We demonstrate the proposed methods by using sex-specific mortality data, and the forecast performances are compared with several existing models, including the independent functional data model and the Product-Ratio model.