The Importance of Year of Birth in Two-Dimensional Mortality Data

Late-life mortality patterns are of crucial interest to actuaries assessing longevity risk. One important explanatory variable is year of birth. We present the results of various analyses demonstrating this, including a statistical model which lends weight to the importance of year-of-birth effects in both population and insured data. We further find that a model based on age and year of birth fits United Kingdom mortality data better than a model based on age and period, suggesting that cohort effects are more significant than period effects. The financial implications of these cohort effects are considerable for portfolios with long-term longevity exposure, such as annuities written by insurance companies and defined benefit pension schemes.