Computing Confidence Intervals for Life Expectancy Estimates of European Regions: a Monte Carlo Simulation Approach

The study proposes a new way to compute confidence intervals for life expectancy estimates, based on Monte Carlo simulations. Taking into account the stochastic variability is particularly relevant for geographical areas with small population size, as the limited number - if any - of death events and/or population at risk, especially at younger ages, may cause fluctuations in the estimates of life expectancies which make it difficult to identify trends. To test its robustness, the method is applied to about 300 complete life tables of European regions computed by Eurostat, representing a variety of mortality patterns and possible issues of data quality/availability. A comparison is also made with other two stochastic methods proposed in the literature (Chiang 1984 and Silcock et al. 2001), as well as sensitivity analyses to assess the impact of different age grouping in the life table.