Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/252333 
Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
Hannover Economic Papers (HEP) No. 688
Verlag: 
Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, Hannover
Zusammenfassung: 
The demographic transition is a phenomenon affecting many industrialized societies. These economies are experiencing a decline in mortality alongside low fertility rates - a situation that puts social security systems under severe pressure. To implement appropriate reform measures, adequate forecasts of the future population structure, specifically in pay-as-you-go systems are needed. We propose a probabilistic approach to forecast the numbers of pensioners in Germany up to 2040, considering trends in population development, labor force participation and early retirement as well as the effects of further pension reforms. A principal component analysis is used for dimensionality reduction and consideration of cross-correlational effects between ageand sex-specific pension rates for both old-age and disability pensions. Time series methods enable the inclusion of autocorrelation effects in the model and the simulation of future uncertainty. The model predicts that, in the median, the numbers of old-age pensioners will increase by almost 5 million individuals from 2017 to 2036, alongside increases in disability pensions by 2036, given the raising of the legal retirement ages following the introduced regulations. After that point, a moderate decrease can be expected. The results show a clear need for further reforms, if the German statutory pension system is to be sustainable in the long run.
Schlagwörter: 
Population Aging
Stochastic Forecasting
Principal Component Analysis
Time Series Analysis
Applied Econometrics
Public Pension Systems
Social Policy
JEL: 
C53
H55
J11
Dokumentart: 
Working Paper

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