Suchergebnisse

Population projections serve various actors at subnational, national, and international levels as a quantitative basis for political and economic decision-making. Usually, the users are no experts in statistics or forecasting and therefore lack the methodological and demographic background to completely understand methods and limitations behind the projections they use to inform further analysis. Our contribution primarily targets that readership. Therefore, we give a brief overview of di erent approaches to population projection and discuss their respective advantages and disadvantages, alongside practical problems in population data and forecasting. Fundamental di erences between deterministic and stochastic approaches are discussed, with special emphasis on the advantages of stochastic approaches. Next to selected projection data available to the public, we show central areas of application of population projections, with an emphasis on Germany

Demographic aging puts social insurance systems under immense pressure as frailty risks increase with age. The statutory long-term care insurance in Germany (GPV), whose society has been aging for decades due to low fertility and decreasing mortality, faces massive future pressure. The present study presents a stochastic outlook on long-term care insurance in Germany until 2045 by forecasting the future number of frail persons who could claim insurance services by severity level with theory-based Monte Carlo simulations. The simulations result in credible intervals for age-, sex- and severity-specific care rates as well as the numbers of persons for all combinations of age, sex and severity by definition of the GPV on an annual basis. The model accounts for demographic trends through time series analysis and considers all realistic epidemiological developments by simulation. The study shows that increases in the general prevalence of disabilities, especially for severe disabilities, caused by the demographic development in Germany are unavoidable, whereas the influence of changes in age-specific care risks does not affect the outcome significantly. The results may serve as a basis for estimating the future demand for care nurses and the financial expenses of the GPV.

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.

"Dieses Papier untersucht die Auswirkungen der sozialabgabenfreien Entgeltumwandlung in der betrieblichen Altersversorgung auf die Rentenversicherung und das Gesamtversorgungsniveau der Versicherten im Alter. Modellrechungen zeigen, dass die Beibehaltung der Sozialabgabenfreiheit zu einem je nach Szenario um etwa 0,1 bis 0,2 Prozentpunkte niedrigeren Rentenversicherungsbeitragssatz und einem um etwa 63 bzw. 39 Cent niedrigeren aktuellen Rentenwert in 2030 führen als ihre Aufhebung. Die Größenordnung der Effekte reduziert sich deutlich, wenn man Verhaltensreaktionen berücksichtigt. Die Beibehaltung führt unter der plausiblen Annahme, dass die betriebliche Altersversorgung eine höhere Rendite erzielt als die gesetzliche Rentenversicherung, zu einer höheren Gesamtversorgung. Da die Beitragsfreiheit der Entgeltumwandlung als Anreiz für die betriebliche Altersvorsorge funktioniert, erscheint diese nach wie vor sinnvoll zur Etablierung eines Mehrsäulensystems der Alterssicherung." (Autorenreferat)