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Event history modeling of world fertility survey data

Author

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  • Adrian Raftery
  • Steven Lewis
  • Akbar Aghajanian
  • Michael Kahn

Abstract

Event history analysis seems ideally suited for the analysis of World Fertility Survey, WFS, data, which consists of full birth histories and related information, but it has not been much used for this purpose. This may be because event history analysis has practical drawbacks for WFS data, namely partial dates, computational burden, the need to take account of five clocks at once and the difficulty of interpreting coefficients. We propose a modeling strategy for the event history analysis of WFS data which overcomes these problems, and we apply it to the previously unanalyzed WFS data from Iran. This yields estimates of the time of onset of fertility decline and the extent to which it was due to compositional changes in the population. It also enables us to determine whether it was a period effect, a cohort effect, or both. These results would have been hard to obtain using other approaches. In addition, the usefulness of ACE as an exploratory tool for determining the best coding of independent variables is illustrated.

Suggested Citation

  • Adrian Raftery & Steven Lewis & Akbar Aghajanian & Michael Kahn, 1996. "Event history modeling of world fertility survey data," Mathematical Population Studies, Taylor & Francis Journals, vol. 6(2), pages 129-153.
    • Handle: RePEc:taf:mpopst:v:6:y:1996:i:2:p:129-153
    DOI: 10.1080/08898489609525426
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    References listed on IDEAS

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    1. Easterlin, Richard A. & Crimmins, Eileen M., 1985. "The Fertility Revolution," University of Chicago Press Economics Books, University of Chicago Press, number 9780226180298, April.
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    Cited by:

    1. Steven M. Lewis & Adrian E. Raftery, 1999. "Bayesian Analysis of Event History Models with Unobserved Heterogeneity via Markov Chain Monte Carlo," Sociological Methods & Research, , vol. 28(1), pages 35-60, August.

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