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Bayesian Estimation of Hispanic Fertility Hazards from Survey and Population Data

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  • Michael S. Rendall
  • Mark S. Handcock
  • Stefan H. Jonsson
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    Abstract

    Previous studies have demonstrated both large efficiency gains and reductions in bias by incorporating population information in regression estimation with sample survey data. These studies, however, assume the population values are exact. This assumption is relaxed here through a Bayesian extension of constrained Maximum Likelihood estimation, applied to 1990s Hispanic fertility. Traditional elements of subjectivity in demographic evaluation and adjustment of survey and population data sources are quantified by this approach, and the inclusion of a larger set of objective data sources is facilitated by it. Compared to estimation from sample survey data only, the Bayesian constrained estimator results in much greater precision in the age pattern of the baseline fertility hazard and, under all but the most extreme assumptions about the uncertainty of the adjusted population data, substantially greater precision about the overall level of the hazard.

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    File URL: http://www.rand.org/content/dam/rand/pubs/working_papers/2007/RAND_WR496.pdf
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    Bibliographic Info

    Paper provided by RAND Corporation Publications Department in its series Working Papers with number 496.

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    Length: 48 pages
    Date of creation: May 2007
    Date of revision:
    Handle: RePEc:ran:wpaper:496

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    Keywords: Bayesian Estimation; Human Fertility; Population Forecasting;

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    1. Imbens, G.W. & Lancaster, T., 1991. "Combining Micro and Macro Data in Microeconometric Models," Harvard Institute of Economic Research Working Papers 1578, Harvard - Institute of Economic Research.
    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.
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