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Stochastic Forecasting of Labor Supply and Population: An Integrated Model

Author

Listed:
  • Johann Fuchs

    (Institute for Employment Research)

  • Doris Söhnlein

    (Institute for Employment Research)

  • Brigitte Weber

    (Institute for Employment Research)

  • Enzo Weber

    (Institute for Employment Research
    University of Regensburg)

Abstract

This paper presents a stochastic model to forecast the German population and labor supply until 2060. Within a cohort-component approach, our population forecast applies principal components analysis to birth, mortality, emigration, and immigration rates, which allows for the reduction of dimensionality and accounts for correlation of the rates. Labor force participation rates are estimated by means of an econometric time series approach. All time series are forecast by stochastic simulation using the bootstrap method. As our model also distinguishes between German and foreign nationals, different developments in fertility, migration, and labor participation could be predicted. The results show that even rising birth rates and high levels of immigration cannot break the basic demographic trend in the long run. An important finding from an endogenous modeling of emigration rates is that high net migration in the long run will be difficult to achieve. Our stochastic perspective suggests therefore a high probability of substantially decreasing the labor supply in Germany.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:poprpr:v:37:y:2018:i:1:d:10.1007_s11113-017-9451-3
    DOI: 10.1007/s11113-017-9451-3
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    3. Patrizio Vanella & Max J. Hassenstein, 2023. "Stochastic Forecasting of Regional Age-Specific Fertility Rates: An Outlook for German NUTS-3 Regions," Mathematics, MDPI, vol. 12(1), pages 1-19, December.
    4. Chartouni Carole & Holzmann Robert & Paez Gustavo N., 2020. "Not everyone is engaged: an innovative approach to measure engagement levels on the labor market," IZA Journal of Labor Policy, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 10(1), pages 1-25, March.
    5. Vanella, Patrizio & Deschermeier, Philipp, 2018. "A Probabilistic Cohort-Component Model for Population Forecasting - The Case of Germany," Hannover Economic Papers (HEP) dp-638, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Christian Dudel & Elke Loichinger & Sebastian Klüsener & Harun Sulak & Mikko Myrskylä, 2021. "The extension of late working life in Germany: trends, inequalities, and the East-West divide," MPIDR Working Papers WP-2021-018, Max Planck Institute for Demographic Research, Rostock, Germany.
    7. 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.

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