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Developing and implementing the UN's probabilistic population projections as a milestone for Bayesian demography: An interview with Adrian Raftery

Author

Listed:
  • Monica Alexander

    (University of Toronto)

  • Adrian E. Raftery

    (University of Washington)

Abstract

Background: Population projections for all countries are published by the United Nations Population Division (UNPD) every two years as part of the World Population Prospects (WPP). Since 2015, probabilistic population projections have been published as part of WPP, produced using Bayesian statistical models. Central to this methodological change was a team of statisticians at the University of Washington, led by Professor Adrian Raftery. Objective: This interview with Adrian Raftery details the history of the UNPD WPP probabilistic population projections, including how the project started, the methodological challenges, main takeaways and lessons, and priorities for future research. Contribution: This interview contributes to the record of scientific thought and the advancement of methodology in demographic research. It demonstrates the evolution of a successful scientific project with large scientific impact and a broader influence on the field of Bayesian demography.

Suggested Citation

  • Monica Alexander & Adrian E. Raftery, 2024. "Developing and implementing the UN's probabilistic population projections as a milestone for Bayesian demography: An interview with Adrian Raftery," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 51(1), pages 1-16.
    • Handle: RePEc:dem:demres:v:51:y:2024:i:1
    DOI: 10.4054/DemRes.2024.51.1
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    References listed on IDEAS

    as
    1. Jonathan Azose & Adrian Raftery, 2015. "Bayesian Probabilistic Projection of International Migration," Demography, Springer;Population Association of America (PAA), vol. 52(5), pages 1627-1650, October.
    2. Mark C. Wheldon & Adrian E. Raftery & Samuel J. Clark & Patrick Gerland, 2013. "Reconstructing Past Populations With Uncertainty From Fragmentary Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(501), pages 96-110, March.
    3. Jakub Bijak & John Bryant, 2016. "Bayesian demography 250 years after Bayes," Population Studies, Taylor & Francis Journals, vol. 70(1), pages 1-19, March.
    4. Adrian E. Raftery & Nevena Lalic & Patrick Gerland, 2014. "Joint probabilistic projection of female and male life expectancy," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(27), pages 795-822.
    5. 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).
    6. Raftery, Adrian E. & Ševčíková, Hana, 2023. "Probabilistic population forecasting: Short to very long-term," International Journal of Forecasting, Elsevier, vol. 39(1), pages 73-97.
    7. 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.
    8. Nan Li & Ronald Lee, 2005. "Coherent mortality forecasts for a group of populations: An extension of the lee-carter method," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 575-594, August.
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    More about this item

    Keywords

    Bayesian demography; methods development; UN population projections; interview;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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