Stochastic population forecast for Germany and its consequence for the German pension system

Arbeitspapier

Population forecasts are crucial for many social, political and economic decisions. Official population projections rely in general on deterministic models which use different scenarios for future vital rates to indicate uncertainty. However, this technique shows substantial weak points such as assuming absolute correlations between the demographic components. In this paper, we argue that a stochastic projection alternative, with no a priori assumptions provides point forecasts and probabilistic prediction intervals for demographic parameters in addition. Age-sex specific population forecast for Germany is derived through a stochastic population renewal process using forecasts of mortality, fertility and migration. Time series models with demographic restrictions are used to describe immigration, emigration and time varying indices of mortality and fertility rates. These models are then used in the simulation of future vital rates to obtain age-specific population forecast using the cohort-component method. The consequence for the German pension system is discussed. To maintain the actual average pension level the premium rate of the present system rises at least by 50% as the old-age ratio nearly doubles by 2040.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2009,009

Classification and Topics

• Classification: Wirtschaft ; Demographic Trends, Macroeconomic Effects, and Forecasts ; Fertility; Family Planning; Child Care; Children; Youth ; Forecasting Models; Simulation Methods ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
• Subject: Demographic forecasting ; population projection ; stochastic demography ; Bevölkerungsprognose ; Prognoseverfahren ; Zeitreihenanalyse ; Stochastischer Prozess ; Theorie ; Altersstruktur der Bevölkerung ; Gesetzliche Rentenversicherung ; Rentenfinanzierung ; Prognose ; Alternde Bevölkerung ; Deutschland

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Härdle, Wolfgang Karl ; Myšičková, Alena
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2009

Further information

• Handle: http://hdl.handle.net/10419/25325
• Last update: 10.03.2025, 11:42 AM CET