IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0179171.html
   My bibliography  Save this article

Probabilistic population aging

Author

Listed:
  • Warren C Sanderson
  • Sergei Scherbov
  • Patrick Gerland

Abstract

We merge two methodologies, prospective measures of population aging and probabilistic population forecasts. We compare the speed of change and variability in forecasts of the old age dependency ratio and the prospective old age dependency ratio as well as the same comparison for the median age and the prospective median age. While conventional measures of population aging are computed on the basis of the number of years people have already lived, prospective measures are computed also taking account of the expected number of years they have left to live. Those remaining life expectancies change over time and differ from place to place. We compare the probabilistic distributions of the conventional and prospective measures using examples from China, Germany, Iran, and the United States. The changes over time and the variability of the prospective indicators are smaller than those that are observed in the conventional ones. A wide variety of new results emerge from the combination of methodologies. For example, for Germany, Iran, and the United States the likelihood that the prospective median age of the population in 2098 will be lower than it is today is close to 100 percent.

Suggested Citation

  • Warren C Sanderson & Sergei Scherbov & Patrick Gerland, 2017. "Probabilistic population aging," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-12, June.
    • Handle: RePEc:plo:pone00:0179171
    DOI: 10.1371/journal.pone.0179171
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0179171
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0179171&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0179171?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Lutz, Wolfgang & Butz, William P. & KC, Samir (ed.), 2014. "World Population and Human Capital in the Twenty-First Century," OUP Catalogue, Oxford University Press, number 9780198703167.
    2. Wolfgang Lutz & Warren Sanderson & Sergei Scherbov, 2001. "The end of world population growth," Nature, Nature, vol. 412(6846), pages 543-545, August.
    3. Warren C. Sanderson & Sergei Scherbov, 2013. "The Characteristics Approach to the Measurement of Population Aging," Population and Development Review, The Population Council, Inc., vol. 39(4), pages 673-685, December.
    4. Warren C. Sanderson & Sergei Scherbov, 2005. "Average remaining lifetimes can increase as human populations age," Nature, Nature, vol. 435(7043), pages 811-813, June.
    5. James W. Vaupel, 2010. "Biodemography of human ageing," Nature, Nature, vol. 464(7288), pages 536-542, March.
    6. Nico Keilman, 2008. "European Demographic Forecasts Have Not Become More Accurate Over the Past 25 Years," Population and Development Review, The Population Council, Inc., vol. 34(1), pages 137-153, March.
    7. Wolfgang Lutz & Warren Sanderson & Sergei Scherbov, 1997. "Doubling of world population unlikely," Nature, Nature, vol. 387(6635), pages 803-805, June.
    8. 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.
    9. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stuart Gietel-Basten & Silvia E Giorguli Saucedo & Sergei Scherbov, 2020. "Prospective measures of aging for Central and South America," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-14, July.
    2. Debasree Das Gupta & David W. S. Wong, 2021. "How “Dependent” Are We? A Spatiotemporal Analysis of the Young and the Older Adult Populations in the US," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 40(6), pages 1221-1252, December.
    3. Michael P. Cameron, 2023. "The measurement of structural ageing – an axiomatic approach," Journal of Population Research, Springer, vol. 40(1), pages 1-22, March.
    4. Warren C. Sanderson & Sergei Scherbov & Patrick Gerland, 2018. "The end of population aging in high-income countries," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 16(1), pages 163-175.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    2. Meng Xu & Helge Brunborg & Joel E. Cohen, 2017. "Evaluating multi-regional population projections with Taylor’s law of mean–variance scaling and its generalisation," Journal of Population Research, Springer, vol. 34(1), pages 79-99, March.
    3. Shulgin, Sergey & Scherbov, Sergey & Zinkina, Yulia & Novikov, Kirill, 2017. "Medical-Demographic Differentiation According to Educational Level," Working Papers 041719, Russian Presidential Academy of National Economy and Public Administration.
    4. Heinz Stefan, 2014. "Uncertainty quantification of world population growth: A self-similar PDF model," Monte Carlo Methods and Applications, De Gruyter, vol. 20(4), pages 261-277, December.
    5. Sergei Scherbov & Dalkhat Ediev, 2016. "Does selection of mortality model make a difference in projecting population ageing?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 34(2), pages 39-62.
    6. Stuart Gietel-Basten & Sergei Scherbov & Warren Sanderson, 2016. "Towards a reconceptualising of population ageing in emerging markets," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 14(1), pages 041-66.
    7. Ediev, Dalkhat M. & Sanderson, Warren C. & Scherbov, Sergei, 2019. "The inverse relationship between life expectancy-induced changes in the old-age dependency ratio and the prospective old-age dependency ratio," Theoretical Population Biology, Elsevier, vol. 125(C), pages 1-10.
    8. Lanza Queiroz, Bernardo & Lobo Alves Ferreira, Matheus, 2021. "The evolution of labor force participation and the expected length of retirement in Brazil," The Journal of the Economics of Ageing, Elsevier, vol. 18(C).
    9. Alho, Juha, 2008. "Aggregation across countries in stochastic population forecasts," International Journal of Forecasting, Elsevier, vol. 24(3), pages 343-353.
    10. David Lam, 2011. "How the World Survived the Population Bomb: Lessons From 50 Years of Extraordinary Demographic History," Demography, Springer;Population Association of America (PAA), vol. 48(4), pages 1231-1262, November.
    11. Frank T. Denton & Byron G. Spencer, 2011. "A Dynamic Extension of the Period Life Table," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 24(34), pages 831-854.
    12. Edouard Debonneuil & Anne Eyraud-Loisel & Frédéric Planchet, 2018. "Can Pension Funds Partially Manage Longevity Risk by Investing in a Longevity Megafund?," Risks, MDPI, vol. 6(3), pages 1-27, July.
    13. Viorela Diaconu & Alyson van Raalte & Pekka Martikainen, 2022. "Why we should monitor disparities in old-age mortality with the modal age at death," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-13, February.
    14. McCarthy, David G. & Wang, Po-Lin, 2021. "Pooling mortality risk in Eurozone state pension liabilities: An application of a Bayesian coherent multi-population cohort-based mortality model," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 459-485.
    15. Tim Riffe & Pil H. Chung & Jeroen Spijker & John MacInnes, 2016. "Time-to-death patterns in markers of age and dependency," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 14(1), pages 229-254.
    16. Hyndman, Rob J. & Booth, Heather, 2008. "Stochastic population forecasts using functional data models for mortality, fertility and migration," International Journal of Forecasting, Elsevier, vol. 24(3), pages 323-342.
    17. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2023. "Thirty years on: A review of the Lee–Carter method for forecasting mortality," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1033-1049.
    18. Daniela Craveiro & Isabel Tiago de Oliveira & Maria Cristina Sousa Gomes & Jorge Malheiros & Maria João Guardado Moreira & João Peixoto, 2019. "Back to replacement migration: A new European perspective applying the prospective-age concept," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(45), pages 1323-1344.
    19. Michael P. Cameron, 2023. "The measurement of structural ageing – an axiomatic approach," Journal of Population Research, Springer, vol. 40(1), pages 1-22, March.
    20. Jorge M. Uribe & Helena Chuliá & Montserrat Guillen, 2018. "Trends in the Quantiles of the Life Table Survivorship Function," European Journal of Population, Springer;European Association for Population Studies, vol. 34(5), pages 793-817, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0179171. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.