IDEAS home Printed from https://ideas.repec.org/p/ssb/dispap/953.html
   My bibliography  Save this paper

Flexible empirical Bayes estimation of local fertility schedules. reducing small area problems and preserving regional variation

Author

Listed:

Abstract

Reliable local demographic schedules are in high demand, but small area problems pose a challenge to estimation. The literature has directed little attention to the opportunities created by increased availability of high-quality geo-coded data. We propose the use of empirical Bayes methods based on a model with three hierarchical geographic levels to predict small area fertility schedules. The proposed model has a flexible specification with respect to age, which allows for detailed age heterogeneity in local fertility patterns. The model limits sampling variability in small areas, captures regional variations effectively, is robust to certain types of model misspecification, and outperforms alternative models in terms of prediction accuracy. The beneficial properties of the model are demonstrated through simulations and estimations on full-count Norwegian population data.

Suggested Citation

  • Stefan Leknes & Sturla A. Løkken, 2021. "Flexible empirical Bayes estimation of local fertility schedules. reducing small area problems and preserving regional variation," Discussion Papers 953, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:953
    as

    Download full text from publisher

    File URL: https://www.ssb.no/en/forskning/discussion-papers/_attachment/452176
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    small area estimation; hierarchical linear models; empirical Bayes method; shrinkage; age-specific fertility;
    All these keywords.

    JEL classification:

    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

    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:ssb:dispap:953. 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: L Maasø (email available below). General contact details of provider: https://edirc.repec.org/data/ssbgvno.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.