IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/3m6va.html
   My bibliography  Save this paper

The Global Burden of Disease fertility forecasts: Summary of the approach used and associated statistical concerns

Author

Listed:
  • Alkema, Leontine

Abstract

BACKGROUND The Global Burden of Disease (GBD) project’s forecasts up to 2100 suggest fertility drops will be even greater in sub-Saharan Africa than the UN Population Division (UNPD) has predicted. OBJECTIVE This reflection summarizes the main assumptions used in the GBD fertility forecasts. I assess the methods used, focusing on high fertility countries and the use of met need for contraceptives as a predictor. RESULTS Based on GBD’s forecasting method, I draw two conclusions. Firstly, GBD fertility forecasts are based on unvalidated assumptions about increasing met need for contraception and may overestimate decreases in fertility in countries with low levels of modern contraceptive use. Secondly, the GBD forecast model for fertility is not a causal model for predicting changes. Claims GBD researchers make about the effect of changing access to family planning on fertility are not informative for guiding policy. Based on the GBD validation exercise, I conclude that the GBD study did not check the performance of the method for predicting left-out fertility data. Also the approach used to compare the predictive performance of UNPD and GBD forecasting methods may give the GBD method an inherent advantage. CONCLUSIONS Communication regarding the GBD method and its findings must avoid causal language and acknowledge the method’s limitations. Future research should examine the performance of the method, especially for countries with low modern contraceptive use. CONTRIBUTION This paper summarizes the GBD fertility forecasting method and indicates three areas of concern about it and its use.

Suggested Citation

  • Alkema, Leontine, 2020. "The Global Burden of Disease fertility forecasts: Summary of the approach used and associated statistical concerns," OSF Preprints 3m6va, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:3m6va
    DOI: 10.31219/osf.io/3m6va
    as

    Download full text from publisher

    File URL: https://osf.io/download/5f3ec80bbacde8009a33c5a9/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/3m6va?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. 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).
    2. 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.
    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. 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.

    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. Heer, Burkhard & Polito, Vito & Wickens, Michael R., 2020. "Population aging, social security and fiscal limits," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    2. Mei Sang & Jing Jiang & Xin Huang & Feifei Zhu & Qian Wang, 2024. "Spatial and temporal changes in population distribution and population projection at county level in China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    3. Dominik Paprotny, 2021. "Convergence Between Developed and Developing Countries: A Centennial Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(1), pages 193-225, January.
    4. Tom Wilson & Irina Grossman & Monica Alexander & Phil Rees & Jeromey Temple, 2022. "Methods for Small Area Population Forecasts: State-of-the-Art and Research Needs," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(3), pages 865-898, June.
    5. 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.
    6. Kevin Rennert & Brian C. Prest & William A. Pizer & Richard G. Newell & David Anthoff & Cora Kingdon & Lisa Rennels & Roger Cooke & Adrian E. Raftery & Hana Sevcikova & Frank Errickson, 2021. "The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 52(2 (Fall)), pages 223-305.
    7. Vanella, Patrizio, 2017. "Age- and Sex-Specific Fertility in Germany until the Year 2040 - The Impact of International Migration," Hannover Economic Papers (HEP) dp-606, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    8. Daphne H. Liu & Adrian E. Raftery, 2020. "How Do Education and Family Planning Accelerate Fertility Decline?," Population and Development Review, The Population Council, Inc., vol. 46(3), pages 409-441, September.
    9. 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.
    10. Asako Ohinata & Dimitrios Varvarigos, 2020. "Demographic Transition and Fertility Rebound in Economic Development," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(4), pages 1640-1670, October.
    11. Michael Pearce & Adrian E. Raftery, 2021. "Probabilistic forecasting of maximum human lifespan by 2100 using Bayesian population projections," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(52), pages 1271-1294.
    12. Liu Qiang & Fernando Rios-Avila & Han Jiqin, 2020. "Is China's Low Fertility Rate Caused by the Population Control Policy?," Economics Working Paper Archive wp_943, Levy Economics Institute.
    13. Jane N. O’Sullivan, 2023. "Demographic Delusions: World Population Growth Is Exceeding Most Projections and Jeopardising Scenarios for Sustainable Futures," World, MDPI, vol. 4(3), pages 1-24, September.
    14. Carl P. Schmertmann & Marcos R. Gonzaga, 2018. "Bayesian Estimation of Age-Specific Mortality and Life Expectancy for Small Areas With Defective Vital Records," Demography, Springer;Population Association of America (PAA), vol. 55(4), pages 1363-1388, August.
    15. Phoebe Koundouri & Georgios I. Papayiannis & Achilleas Vassilopoulos & Athanasios Yannacopoulos, 2022. "A general framework for the generation of probabilistic socioeconomic scenarios and risk quantification concerning food security with application in the Upper Nile river basin," DEOS Working Papers 2203, Athens University of Economics and Business.
    16. Phoebe Koundouri & Georgios I. Papayiannis & Achilleas Vassilopoulos & Athanasios N. Yannacopoulos, 2023. "Probabilistic Scenario-Based Assessment of National Food Security Risks with Application to Egypt and Ethiopia," Papers 2312.04428, arXiv.org, revised Dec 2023.
    17. Philip G. Pardey & Jason M. Beddow & Terrance M. Hurley & Timothy K.M. Beatty & Vernon R. Eidman, 2014. "A Bounds Analysis of World Food Futures: Global Agriculture Through to 2050," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(4), pages 571-589, October.
    18. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    19. Bailey Fosdick & Adrian E. Raftery, 2014. "Regional probabilistic fertility forecasting by modeling between-country correlations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(35), pages 1011-1034.
    20. Niall Newsham & Francisco Rowe, 2021. "Projecting the demographic impact of Syrian migration in a rapidly ageing society, Germany," Journal of Geographical Systems, Springer, vol. 23(2), pages 231-261, April.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:osfxxx:3m6va. 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.