ISSN:
1869-8999
Inhalt:
Industrialised economies are experiencing a decline in mortality alongside low fertility rates - a situation that puts social security systems under severe pressure. Population ageing is associated not only with longer periods of pension claims but also smaller cohorts eventually entering the labour market. This threatens the sustainability of pay-as-you-go social security systems for implementing or further improving appropriate reform measures; adequate forecasts of the future population structure are needed. We propose a probabilistic approach to forecast the number of pensions in Germany up to 2040. Our model considers trends in population development, labour force participation, and early retirement, as well as the effects of pension reforms. Principal component analysis is used to manage the high degree of complexity involved in forecasting trends in old-age and disability pension claims, which arises because of cross-correlations between old-age and disability pension rates, different age groups, and gender. Time series methods enable the inclusion of autocorrelations of the pension rate time series in the model. Monte Carlo simulation is used to quantify future risk. The latter is an important feature of our model, as the future development of the population and, eventually, the pension claims and the financial burden resulting from those claims, are highly stochastic. The model predicts that, in the median trajectory, the number of old-age pensions will increase by almost 5 million between 2017 and 2036, alongside increases in the number of disability pensions by 2036. These numbers take account of the increase in legal retirement ages as part of the 2007 pension reform. After the mid-2030s, however, a moderate decrease can be expected. The results show a clear need for further reforms, especially in the medium term.
In:
Comparative population studies, Wiesbaden : Bundesinst. für Bevölkerungsforschung, 2010, 47(2022), Seite 87-118, 1869-8999
In:
volume:47
In:
year:2022
In:
pages:87-118
Sprache:
Englisch
Schlagwort(e):
Aufsatz in Zeitschrift
DOI:
10.12765/CPoS-2022-05
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