Understanding the systematic relationship between period and cohort life expectancy and how the relationship evolves over time are critical issues in formulating the design of retirement income products, evaluating the actuarial balance of pension schemes, and more generally for all analyses where demographic projections are involved. In this study, estimates of the life expectancy gap at all ages are performed using data for 1960–2018 from the Human Mortality Database and projections are generated through 2050 for the 42 national populations, disaggregated by sex. Contrary to previous research that often uses a single deemed to be «best» model to forecast mortality rates, we use a novel adaptive Bayesian Model Ensemble of heterogeneous parametric generalized age-period-cohort stochastic mortality models, principal component methods, and smoothing approaches. The procedure involves both the selection of the model confidence set and the determination of optimal weights. Model-averaged Bayesian credible prediction intervals are derived accounting for both the uncertainty arising from model error and parameter uncertainty. With intergenerational actuarial fairness and neutrality as the guiding principles the study then explores potential policy interventions to address the consequences of the life expectancy gap - spanning over adjustments in the accumulation, benefit determination, and payout stages. Comprehensive numerical results are provided for two policy options: (i) introducing a sustainability factor; and (ii) conditional pension indexation. The results show that: (i) the life expectancy gap is positive and significant for almost all countries and years studied, (ii) it will continue to increase, (iii) the magnitude of the subsidy rates between generations can be sizeable demanding important initial pension benefit reduction and/or a gradual diminution in the annual indexation rate of pensions to correct them.

在制定退休收入产品的设计，评估养老金计划的精算余额以及更广泛地涉及涉及人口预测的所有分析时，了解周期与队列预期寿命之间的系统关系以及这种关系如何随时间演变是至关重要的问题。在这项研究中，使用人类死亡率数据库中1960–2018年的数据估算了各个年龄段的预期寿命差距，并按性别分列了2050年全国人口的预测。与以前的研究通常使用单个被认为是“最佳”模型来预测死亡率的研究相反，我们使用了一种新的自适应贝叶斯模型组合，该模型是异类参数化广义年龄组同期随机死亡率模型，主成分方法，和平滑方法。该过程涉及模型置信度集的选择和最佳权重的确定。得出模型平均贝叶斯可信预测间隔，其中考虑了模型误差和参数不确定性所引起的不确定性。本研究以代际精算公平性和中立性为指导原则，然后探索潜在的政策干预措施来解决预期寿命差距的后果-跨越积累，福利确定和支出阶段的调整。提供了两种政策选择的综合数值结果：（i）引入可持续性因素；（ii）有条件的退休金指数化。结果表明：（i）预期寿命差距在几乎所有研究的国家和地区都是正的，并且是显着的，