IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v30y2014i35.html
   My bibliography  Save this article

Regional probabilistic fertility forecasting by modeling between-country correlations

Author

Listed:
  • Bailey Fosdick

    (Duke University)

  • Adrian E. Raftery

    (University of Washington)

Abstract

Background: The United Nations (UN) Population Division constructs probabilistic projections for the total fertility rate (TFR) using the Bayesian hierarchical model of Alkema et al. (2011), which produces predictive distributions of the TFR for individual countries. The UN is interested in publishing probabilistic projections for aggregates of countries, such as regions and trading blocs. This requires joint probabilistic projections of future countryspecific TFRs, taking account of the correlations between them. Objective: We propose an extension of the Bayesian hierarchical model that allows for probabilistic projection of aggregate TFR for any set of countries. Methods: We model the correlation between country forecast errors as a linear function of time invariant covariates, namely whether the countries are contiguous, whether they had a common colonizer after 1945, and whether they are in the same UN region. The resulting correlation model is incorporated into the Bayesian hierarchical model’s error distribution. Results: We produce predictive distributions of TFR for 1990-2010 for each of the UN's primary regions. We find that the proportions of the observed values that fall within the prediction intervals from our method are closer to their nominal levels than those produced by the current model. Conclusions: Our results suggest that a substantial proportion of the correlation between forecast errors for TFR in different countries is due to the countries' geographic proximity to one another, and that if this correlation is accounted for, the quality of probabilistic projections of TFR for regions and other aggregates is improved.

Suggested Citation

  • 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.
    • Handle: RePEc:dem:demres:v:30:y:2014:i:35
    DOI: 10.4054/DemRes.2014.30.35
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol30/35/30-35.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4054/DemRes.2014.30.35?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. Nico Keilman & Dinh Quang Pham, 2004. "Empirical errors and predicted errors in fertility, mortality and migration forecasts in the European Economic Area," Discussion Papers 386, Statistics Norway, Research Department.
    2. Wolfgang Lutz & Warren Sanderson & Sergei Scherbov, 2001. "The end of world population growth," Nature, Nature, vol. 412(6846), pages 543-545, August.
    3. Mayer, Thierry & Zignago, Soledad, 2006. "Notes on CEPII’s distances measures," MPRA Paper 26469, University Library of Munich, Germany.
    4. Alho, Juha, 2008. "Aggregation across countries in stochastic population forecasts," International Journal of Forecasting, Elsevier, vol. 24(3), pages 343-353.
    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. Bailey K. Fosdick & Adrian E. Raftery, 2012. "Estimating the Correlation in Bivariate Normal Data With Known Variances and Small Sample Sizes," The American Statistician, Taylor & Francis Journals, vol. 66(1), pages 34-41, February.
    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. D. R. Cox, 2004. "A note on pseudolikelihood constructed from marginal densities," Biometrika, Biometrika Trust, vol. 91(3), pages 729-737, September.
    9. 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.
    10. Wolfgang Lutz & Warren Sanderson & Sergei Scherbov, 1997. "Doubling of world population unlikely," Nature, Nature, vol. 387(6635), pages 803-805, June.
    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. 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.
    2. 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.
    3. Lin Ma & Manhua Wu & Xiujuan Tian & Guanheng Zheng & Qinchuan Du & Tian Wu, 2019. "China’s Provincial Vehicle Ownership Forecast and Analysis of the Causes Influencing the Trend," Sustainability, MDPI, vol. 11(14), pages 1-26, July.
    4. 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.
    5. 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.
    6. Hana Sevcikova & Adrian E. Raftery & Patrick Gerland, 2018. "Probabilistic projection of subnational total fertility rates," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(60), pages 1843-1884.

    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. 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.
    2. 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.
    3. 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).
    4. 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.
    5. Alho, Juha, 2008. "Aggregation across countries in stochastic population forecasts," International Journal of Forecasting, Elsevier, vol. 24(3), pages 343-353.
    6. 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.
    7. Guy Abel & Jakub Bijak & Jonathan J. Forster & James Raymer & Peter W.F. Smith & Jackie S.T. Wong, 2013. "Integrating uncertainty in time series population forecasts: An illustration using a simple projection model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(43), pages 1187-1226.
    8. 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.
    9. 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.
    10. Koundouri, Phoebe & Papayiannis, Georgios I. & Vassilopoulos, Achilleas & Yannacopoulos, Athanasios N., 2023. "Probabilistic Scenario-Based Assessment of National Food Security Risks with Application to Egypt and Ethiopia," MPRA Paper 122007, University Library of Munich, Germany.
    11. 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.
    12. 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.
    13. David J Sharrow & Samuel J Clark & Adrian E Raftery, 2014. "Modeling Age-Specific Mortality for Countries with Generalized HIV Epidemics," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-10, May.
    14. 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.
    15. Francesco Billari & Rebecca Graziani & Eugenio Melilli, 2014. "Stochastic Population Forecasting Based on Combinations of Expert Evaluations Within the Bayesian Paradigm," Demography, Springer;Population Association of America (PAA), vol. 51(5), pages 1933-1954, October.
    16. 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.
    17. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    18. 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.
    19. 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.
    20. 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.

    More about this item

    Keywords

    forecasting; probabilistic projection; total fertility rate (TFR); correlation; aggregation; pseudolikelihood;
    All these keywords.

    JEL classification:

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

    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:dem:demres:v:30:y:2014:i:35. 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: Editorial Office (email available below). General contact details of provider: https://www.demogr.mpg.de/ .

    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.