IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v108y2013i501p96-110.html
   My bibliography  Save this article

Reconstructing Past Populations With Uncertainty From Fragmentary Data

Author

Listed:
  • Mark C. Wheldon
  • Adrian E. Raftery
  • Samuel J. Clark
  • Patrick Gerland

Abstract

Current methods for reconstructing human populations of the past by age and sex are deterministic or do not formally account for measurement error. We propose a method for simultaneously estimating age-specific population counts, fertility rates, mortality rates, and net international migration flows from fragmentary data that incorporates measurement error. Inference is based on joint posterior probability distributions that yield fully probabilistic interval estimates. It is designed for the kind of data commonly collected in modern demographic surveys and censuses. Population dynamics over the period of reconstruction are modeled by embedding formal demographic accounting relationships in a Bayesian hierarchical model. Informative priors are specified for vital rates, migration rates, population counts at baseline, and their respective measurement error variances. We investigate calibration of central posterior marginal probability intervals by simulation and demonstrate the method by reconstructing the female population of Burkina Faso from 1960 to 2005. Supplementary materials for this article are available online and the method is implemented in the R package "popReconstruct."

Suggested Citation

  • 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.
    • Handle: RePEc:taf:jnlasa:v:108:y:2013:i:501:p:96-110
    DOI: 10.1080/01621459.2012.737729
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2012.737729
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01621459.2012.737729?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Arkadiusz Wiśniowski, 2017. "Combining Labour Force Survey data to estimate migration flows: the case of migration from Poland to the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 185-202, January.
    2. Miikka Voutilainen & Jouni Helske & Harri Högmander, 2020. "A Bayesian Reconstruction of a Historical Population in Finland, 1647–1850," Demography, Springer;Population Association of America (PAA), vol. 57(3), pages 1171-1192, June.
    3. Arkadiusz Wiśniowski & Peter Smith & Jakub Bijak & James Raymer & Jonathan Forster, 2015. "Bayesian Population Forecasting: Extending the Lee-Carter Method," Demography, Springer;Population Association of America (PAA), vol. 52(3), pages 1035-1059, June.
    4. Wazir Asif & Goujon Anne, 2021. "Exploratory Assessment of the Census of Pakistan Using Demographic Analysis," Journal of Official Statistics, Sciendo, vol. 37(3), pages 719-750, September.
    5. Yigang Wei & Zhichao Wang & Huiwen Wang & Yan Li & Zhenyu Jiang, 2019. "Predicting population age structures of China, India, and Vietnam by 2030 based on compositional data," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-42, April.
    6. 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.

    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:taf:jnlasa:v:108:y:2013:i:501:p:96-110. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UASA20 .

    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.