IDEAS home Printed from https://ideas.repec.org/p/hwe/seecdp/1302.html
   My bibliography  Save this paper

Regional fertility data analysis: A small area Bayesian approach

Author

Listed:
  • Eduardo A. Castro

    (Department of Social, Political and Territorial Sciences, University of Aveiro)

  • Zhen Zhang

    (Department of Statistics and Probability, Michigan State University)

  • Arnab Bhattacharjee

    (Department of Economics and Spatial Economics and Econometrics Centre (SEEC), Heriot-Watt University)

  • José M. Martins

    (Department of Social, Political and Territorial Sciences, University of Aveiro)

  • Taps Maiti

Abstract

Accurate estimation of demographic variables such as mortality, fertility and migrations, by age groups and regions, is important for analyses and policy. However, traditional estimates based on within cohort counts are often inaccurate, particularly when the sub-populations considered are small. We use small area Bayesian statistics to develop a model for age-specific fertility rates. In turn, such small area estimation requires accurate descriptions of spatial and cross-section dependence. The proposed methodology uses spatial clustering methods to estimate an adjacency matrix that captures such dependence more adequately. The model is then used to estimate agespecific fertility rates and total fertility rates at the regional NUTS III area level for Portugal. The paper makes important contributions to small area Bayesian statistics in a spatial domain focusing on estimation of fertility rates. The estimates obtained are more accurate and adequately represent uncertainty in the estimates, and are therefore very useful for demographic policy in Portugal.

Suggested Citation

  • Eduardo A. Castro & Zhen Zhang & Arnab Bhattacharjee & José M. Martins & Taps Maiti, 2013. "Regional fertility data analysis: A small area Bayesian approach," SEEC Discussion Papers 1302, Spatial Economics and Econometrics Centre, Heriot Watt University.
  • Handle: RePEc:hwe:seecdp:1302
    as

    Download full text from publisher

    File URL: http://seec.hw.ac.uk/images/discussionpapers/SEEC_DiscussionPaper_No2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Renato Assunção & Carl Schmertmann & Joseph Potter & Suzana Cavenaghi, 2005. "Empirical bayes estimation of demographic schedules for small areas," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 537-558, August.
    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)

    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. 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.
    2. 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).
    3. 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.
    4. 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.
    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. Michael S. Rendall & Mark S. Handcock & Stefan H. Jonsson, 2007. "Bayesian Estimation of Hispanic Fertility Hazards from Survey and Population Data," Working Papers WR-496, RAND Corporation.
    7. Maria Tzitiridou-Chatzopoulou & Georgia Zournatzidou & Michael Kourakos, 2024. "Predicting Future Birth Rates with the Use of an Adaptive Machine Learning Algorithm: A Forecasting Experiment for Scotland," IJERPH, MDPI, vol. 21(7), pages 1-13, June.
    8. Jessica Nisén & Sebastian Klüsener & Johan Dahlberg & Lars Dommermuth & Aiva Jasilioniene & Michaela Kreyenfeld & Trude Lappegård & Peng Li & Pekka Martikainen & Karel Neels & Bernhard Riederer & Sask, 2021. "Educational Differences in Cohort Fertility Across Sub-national Regions in Europe," European Journal of Population, Springer;European Association for Population Studies, vol. 37(1), pages 263-295, March.
    9. 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.
    10. 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.
    11. Corey Sparks & Joey Campbell, 2014. "An Application of Bayesian Methods to Small Area Poverty Rate Estimates," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 33(3), pages 455-477, June.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Matt Ruther & Galen Maclaurin & Stefan Leyk & Barbara Buttenfield & Nicholas Nagle, 2013. "Validation of spatially allocated small area estimates for 1880 Census demography," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(22), pages 579-616.
    17. 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.
    18. 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.
    19. 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.
    20. 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.

    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:hwe:seecdp:1302. 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: Colin Miller (email available below). General contact details of provider: https://edirc.repec.org/data/dehwuuk.html .

    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.