A probabilistic projection of beneficiaries of long-term care insurance in Germany by severity of disability

Patrizio Vanella (), Moritz Heß () and Christina B. Wilke ()
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Patrizio Vanella: Gottfried Wilhelm Leibniz Universität Hannover
Moritz Heß: Universität Bremen
Christina B. Wilke: FOM Hochschulzentrum Bremen

Quality & Quantity: International Journal of Methodology, 2020, vol. 54, issue 3, No 11, 943-974

Abstract: Abstract 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.

Keywords: Long-term care; Social insurance; Monte Carlo simulation; Stochastic forecasting; Disability risks; Social policy (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11135-020-00968-w

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