A Probabilistic Cohort-Component Model for Population Forecasting – the Case of Germany

Patrizio Vanella , Helmholtz-Zentrum für Infektionsforschung
Philipp Deschermeier, Institut Wohnen und Umwelt

The future development of population size and structure is of importance since planning in many areas of politics and business is conducted based on expectations about the future makeup of the population. Countries with both decreasing mortality and low fertility rates, which is the case for most countries in Europe, urgently need adequate population forecasts to identify future problems regarding social security systems as one determinant of overall macroeconomic development. This contribution proposes a stochastic cohort-component model that uses simulation tech-niques based on stochastic models for fertility, migration and mortality to forecast the popula-tion by age and sex. We specifically focused on quantifying the uncertainty of future devel-opment as previous studies have tended to underestimate future risk. The model is applied to forecast the population of Germany until 2045. The results provide detailed insight into the future population structure, disaggregated into both sexes and age groups by year. Moreover, the uncertainty in the forecast is quantified as prediction intervals for each subgroup.

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 Presented in Session P3. Poster Session Migration, Economics, Environment, Methods, History and Policy