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Fitting Observed Demographic Rates with the Multiexponential Model Schedule: An Assessment of Two Estimation Programs

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  • Andrei Rogers
  • James Raymer

Abstract

The process of finding the best fitting model can often be very time consuming and tedious. Most computer programs are very specialized, and many require initial parameter estimates to fit a particular curve. Those that are most useful are ones that are versatile in applications, and ones that allow inputs of “rough†parameter estimates for finding the optimal ones. This paper focuses on current approaches for fitting observed age†specific demographic data with the multiexponential model schedule and uses two curve†fitting computer programs: MODEL and TableCurve2D. These two programs are assessed according to how well, and how simply, they can be used to fit age†specific fertility, mortality, and migration rates.

Suggested Citation

  • Andrei Rogers & James Raymer, 1999. "Fitting Observed Demographic Rates with the Multiexponential Model Schedule: An Assessment of Two Estimation Programs," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 11(1), pages 1-10, March.
    • Handle: RePEc:bla:revurb:v:11:y:1999:i:1:p:1-10
    DOI: 10.1111/1467-940X.00001
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    Cited by:

    1. Bernard Baffour & James Raymer, 2019. "Estimating multiregional survivorship probabilities for sparse data: An application to immigrant populations in Australia, 1981–2011," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(18), pages 463-502.
    2. Aude Bernard & Martin Bell, 2015. "Smoothing internal migration age profiles for comparative research," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(33), pages 915-948.
    3. Andrei Rogers & Luis Castro & Megan Lea, 2005. "Model Migration Schedules: Three Alternative Linear Parameter Estimation Methods," Mathematical Population Studies, Taylor & Francis Journals, vol. 12(1), pages 17-38.

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