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Bayes plus Brass: Estimating total fertility for many small areas from sparse census data

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  • Carl P. Schmertmann
  • Suzana M. Cavenaghi
  • Renato M. Assunção
  • Joseph E. Potter

Abstract

Estimates of fertility in small areas are valuable for analysing demographic change, and important for local planning and population projection. In countries lacking complete vital registration, however, small-area estimates are possible only from sparse survey or census data that are potentially unreliable. In these circumstances estimation requires new methods for old problems: procedures must be automated if thousands of estimates are required; they must deal with extreme sampling variability in many areas; and they should also incorporate corrections for possible data errors. We present a two-step procedure for estimating total fertility in such circumstances and illustrate it by applying the method to data from the 2000 Brazilian Census for over 5,000 municipalities. Our proposed procedure first smoothes local age-specific rates using Empirical Bayes methods and then applies a new variant of Brass's P/F parity correction procedure that is robust to conditions of rapid fertility decline. Supplementary material at the project website http://schmert.net/BayesBrass will allow readers to replicate all the authors' results in this paper using their data and programs .

Suggested Citation

  • Carl P. Schmertmann & Suzana M. Cavenaghi & Renato M. Assunção & Joseph E. Potter, 2013. "Bayes plus Brass: Estimating total fertility for many small areas from sparse census data," Population Studies, Taylor & Francis Journals, vol. 67(3), pages 255-273, November.
  • Handle: RePEc:taf:rpstxx:v:67:y:2013:i:3:p:255-273
    DOI: 10.1080/00324728.2013.795602
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    Cited by:

    1. Queiroz, Bernardo L & Lima, Everton & Freire, Flávio & Gonzaga, Marcos Roberto, 2017. "Temporal and spatial estimates of adult mortality for small areas in Brazil, 1980-2010," OSF Preprints jk67t, Center for Open Science.
    2. 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.
    3. Sakshaug Joseph W. & Wiśniowski Arkadiusz & Ruiz Diego Andres Perez & Blom Annelies G., 2019. "Supplementing Small Probability Samples with Nonprobability Samples: A Bayesian Approach," Journal of Official Statistics, Sciendo, vol. 35(3), pages 653-681, September.

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