This study extends existing mortality prediction frameworks by incorporating information borrowed from population–gender–age subgroups that exhibit similar mortality patterns. The borrowed information is integrated into classical mortality models to improve the accuracy of future mortality rate forecasts. To capture structural similarities among mortality trajectories, several distance measures are evaluated in combination with four linkage methods, particularly when each subgroup comprises multiple age-specific mortality trajectories. Extensive empirical analyses using data from the Human Mortality Database demonstrate the superior predictive performance of the proposed approach.
Câmpeanu et al. (Mon,) studied this question.