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Population constraints on pooled surveys in demographic hazard modeling

Author

Listed:
  • Michael S. Rendall
  • Ryan Admiraal
  • Alessandra De Rose
  • Paola Di Giulio

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Mark S. Handcock
  • Filomena Racioppi

Abstract

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total survey sample size.

Suggested Citation

  • Michael S. Rendall & Ryan Admiraal & Alessandra De Rose & Paola Di Giulio & Mark S. Handcock & Filomena Racioppi, 2006. "Population constraints on pooled surveys in demographic hazard modeling," MPIDR Working Papers WP-2006-039, Max Planck Institute for Demographic Research, Rostock, Germany.
    • Handle: RePEc:dem:wpaper:wp-2006-039
    DOI: 10.4054/MPIDR-WP-2006-039
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    References listed on IDEAS

    as
    1. Guido W. Imbens & Tony Lancaster, 1994. "Combining Micro and Macro Data in Microeconometric Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 655-680.
    2. Judith K. Hellerstein & Guido W. Imbens, 1999. "Imposing Moment Restrictions From Auxiliary Data By Weighting," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 1-14, February.
    3. Mark Handcock & Sami Huovilainen & Michael Rendall, 2000. "Combining registration-system and survey data to estimate birth probabilities," Demography, Springer;Population Association of America (PAA), vol. 37(2), pages 187-192, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Italy; fertility;

    JEL classification:

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

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