Analyzing the impact of mortality assumptions on projection outcome with the Probabilistic Population Projection Model

Christina Bohk, University of Rostock
Roland Rau, University of Rostock

Mortality is one of the three core demographic parameters that drive population growth. In recent years, populations of many highly developed countries age due to increasing life expectancy and decreasing fertility. A growing proportion of elderly people is a key characteristic of aging populations. As elderly people are mostly affected by mortality, generating mortality assumptions will gain more importance in population projections. To analyze the impact of mortality assumptions on the projection outcome, we conduct a population projection with real-world data for Germany with the Probabilistic Population Projection Model (PPPM) that has several methodological advantages (in generating mortality assumptions and analyzing projected outcome) compared to typical projection models. An unique feature of the PPPM is the association of the projection outcome and its generating assumptions for each projection trial. This feature allows us to combine selected result paths to a distribution that have one or more certain assumptions in common. Therefore, we conduct one projection with multiple mortality assumptions, and compare thereafter result distributions that are a combination of result paths with different mortality assumptions. Our results indicate, that mortality assumptions indeed have a major impact on projected total population size in older populations, and that common probabilistic projection approaches can underestimate future uncertainty due to their restriction to only one assumption with stochastic variation for each model parameter.