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Prevalence and Economic Costs of Absenteeism in an Aging Population—A Quasi-Stochastic Projection for Germany

Author

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  • Patrizio Vanella

    (Helmholtz Centre for Infection Research, Epidemiology Department, 38124 Brunswick, Germany
    Chair of Empirical Methods in Social Science and Demography, Faculty of Economics and Sociology, University of Rostock, 18057 Rostock, Germany)

  • Christina Benita Wilke

    (Chair of Economics, Faculty of Economics, FOM University of Applied Sciences, Hochschulzentrum Bremen, 28359 Bremen, Germany)

  • Doris Söhnlein

    (Institute for Employment Research (IAB), Forecasts and Macroeconomic Analyses Department, 90478 Nürnberg, Germany)

Abstract

Demographic change is leading to the aging of German society. As long as the baby boom cohorts are still of working age, the working population will also age—and decline as soon as this baby boom generation gradually reaches retirement age. At the same time, there has been a trend toward increasing absenteeism (times of inability to work) in companies since the zero years, with the number of days of absence increasing with age. We present a novel stochastic forecast approach that combines population forecasting with forecasts of labor force participation trends, considering epidemiological aspects. For this, we combine a stochastic Monte Carlo-based cohort-component forecast of the population with projections of labor force participation rates and morbidity rates. This article examines the purely demographic effect on the economic costs associated with such absenteeism due to the inability to work. Under expected future employment patterns and constant morbidity patterns, absenteeism is expected to be close to 5 percent by 2050 relative to 2020, associated with increasing economic costs of almost 3 percent. Our results illustrate how strongly the pronounced baby boom/baby bust phenomenon determines demographic development in Germany in the midterm.

Suggested Citation

  • Patrizio Vanella & Christina Benita Wilke & Doris Söhnlein, 2022. "Prevalence and Economic Costs of Absenteeism in an Aging Population—A Quasi-Stochastic Projection for Germany," Forecasting, MDPI, vol. 4(1), pages 1-23, March.
    • Handle: RePEc:gam:jforec:v:4:y:2022:i:1:p:21-393:d:771880
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    References listed on IDEAS

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    1. Johann Fuchs & Doris Söhnlein & Brigitte Weber & Enzo Weber, 2018. "Stochastic Forecasting of Labor Supply and Population: An Integrated Model," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(1), pages 33-58, February.
    2. Singh-Manoux, A. & Guéguen, A. & Ferrie, J. & Shipley, M. & Martikainen, P. & Bonenfant, S. & Goldberg, M. & Marmot, M., 2008. "Gender differences in the association between morbidity and mortality among middle-aged men and women," American Journal of Public Health, American Public Health Association, vol. 98(12), pages 2251-2257.
    3. Patrizio Vanella & Philipp Deschermeier & Christina B. Wilke, 2020. "An Overview of Population Projections—Methodological Concepts, International Data Availability, and Use Cases," Forecasting, MDPI, vol. 2(3), pages 1-18, September.
    4. Patrizio Vanella & Christian Wiessner & Anja Holz & Gérard Krause & Annika Möhl & Sarah Wiegel & Berit Lange & Heiko Becher, 2022. "Pitfalls and solutions in case fatality risk estimation – A multi-country analysis on the effects of demographics, surveillance, time lags between case reports and deaths and healthcare system capacity on COVID-19 CFR estimates," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 20(1), pages 167-193.
    5. Beznoska, Martin & Pimpertz, Jochen & Stockhausen, Maximilian, 2021. "Führt eine Bürgerversicherung zu mehr Solidarität? Eine Vermessung des Solidaritätsprinzips in der gesetzlichen Krankenversicherung," IW-Analysen, Institut der deutschen Wirtschaft (IW) / German Economic Institute, volume 127, number 143.
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