The importance of year of birth in two-dimensional mortality data

Document description

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 in both population and insured data. We further find that a model based on age or year of birth fits United Kingdom mortality data better than a model based on age and period, suggesting that cohorts are more significant than period effects. The financial implications of these cohorts effects are more significant than period effects. The financial imlications 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. Keywords: mortality improvements; cohorts; early life conditions; moving averages; kernel smoothing; penalised splines