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An Overview of Population Projections—Methodological Concepts, International Data Availability, and Use Cases

Author

Listed:
  • Patrizio Vanella

    (Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), 38124 Brunswick, Germany)

  • Philipp Deschermeier

    (Institute for Housing and Environment (IWU), 64295 Darmstadt, Germany
    Equal contribution.)

  • Christina B. Wilke

    (Chair of Economics, FOM University of Applied Sciences, 28359 Bremen, Germany
    Equal contribution.)

Abstract

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 different approaches to population projection and discuss their respective advantages and disadvantages, alongside practical problems in population data and forecasting. Fundamental differences 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.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jforec:v:2:y:2020:i:3:p:19-363:d:408030
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    References listed on IDEAS

    as
    1. Ingrid Hamm & Helmut Seitz & Martin Werding (ed.), 2008. "Demographic Change in Germany," Springer Books, Springer, number 978-3-540-68137-3, December.
    2. Ronald Lee & Shripad Tuljapurkar, 1998. "Stochastic Forecasts for Social Security," NBER Chapters, in: Frontiers in the Economics of Aging, pages 393-428, National Bureau of Economic Research, Inc.
    3. F. C. Billari & R. Graziani & E. Melilli, 2012. "Stochastic population forecasts based on conditional expert opinions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(2), pages 491-511, April.
    4. Adrian Raftery & Jennifer Chunn & Patrick Gerland & Hana Ševčíková, 2013. "Bayesian Probabilistic Projections of Life Expectancy for All Countries," Demography, Springer;Population Association of America (PAA), vol. 50(3), pages 777-801, June.
    5. 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.
    6. Ševčíková, Hana & Alkema, Leontine & Raftery, Adrian, 2011. "bayesTFR: An R package for Probabilistic Projections of the Total Fertility Rate," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i01).
    7. Deschermeier, Philipp & Henger, Ralph & Seipelt, Björn & Voigtländer, Michael, 2017. "Wohnungsmangel in den Städten, Leerstand auf dem Land," IW-Kurzberichte 44.2017, Institut der deutschen Wirtschaft (IW) / German Economic Institute.
    8. Bloom, David E. & Kuhn, Michael & Prettner, Klaus, 2017. "Africa'S Prospects For Enjoying A Demographic Dividend," Journal of Demographic Economics, Cambridge University Press, vol. 83(1), pages 63-76, March.
    9. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    10. Maria Rita Testa & Francesco Rampazzo, 2018. "From intentions to births: paths of realisation in a multi-dimensional life course," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 16(1), pages 177-198.
    11. Deschermeier, Philipp, 2016. "Einfluss der Zuwanderung auf die demografische Entwicklung in Deutschland," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, vol. 43(2), pages 21-38.
    12. Tom Wilson & Huw Brokensha & Francisco Rowe & Ludi Simpson, 2018. "Insights from the Evaluation of Past Local Area Population Forecasts," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(1), pages 137-155, February.
    13. David E. Bloom & Michael Kuhn & Klaus Prettner, 2016. "Africa’s Prospects for Enjoying a Demographic Dividend," VID Working Papers 1604, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    14. Hyndman, Rob J. & Shahid Ullah, Md., 2007. "Robust forecasting of mortality and fertility rates: A functional data approach," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4942-4956, June.
    15. Niels Kooiman & Jan Latten & Marco Bontje, 2018. "Human Capital Migration: A Longitudinal Perspective," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 109(5), pages 644-660, December.
    16. Leontine Alkema & Adrian Raftery & Patrick Gerland & Samuel Clark & François Pelletier & Thomas Buettner & Gerhard Heilig, 2011. "Probabilistic Projections of the Total Fertility Rate for All Countries," Demography, Springer;Population Association of America (PAA), vol. 48(3), pages 815-839, August.
    17. Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
    18. Guangqing Chi & David Marcouiller, 2011. "Isolating the Effect of Natural Amenities on Population Change at the Local Level," Regional Studies, Taylor & Francis Journals, vol. 45(4), pages 491-505.
    19. Clara Mulder, 2006. "Population and housing," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(13), pages 401-412.
    20. Samir Soneji & Gary King, 2012. "Statistical Security for Social Security," Demography, Springer;Population Association of America (PAA), vol. 49(3), pages 1037-1060, August.
    21. Nico Keilman & Dinh Quang Pham & Arve Hetland, 2002. "Why population forecasts should be probabilistic - illustrated by the case of Norway," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 6(15), pages 409-454.
    22. Charlotte Höhn & Ralf Mai & Frank Micheel, 2008. "Demographic Change in Germany," Springer Books, in: Ingrid Hamm & Helmut Seitz & Martin Werding (ed.), Demographic Change in Germany, pages 9-33, Springer.
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    Cited by:

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    2. 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.

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