Beschreibung:
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