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Model Migration Schedules: Three Alternative Linear Parameter Estimation Methods

Author

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  • Andrei Rogers
  • Luis Castro
  • Megan Lea

Abstract

Observed schedules of migration rates exhibit strong regularities in age patterns. These regularities may be captured and represented by a mathematical expression known as the multiexponential model migration schedule. Fitting this function to empirical data requires non-linear regression methods and often some experimentation with alternative initial estimates of the parameters. Simpler, linear methods of estimation are adequate for most applications. These may be carried out with hand calculators or simple spreadsheet-based calculations on the computer. Such methods are studied and appear to perform satisfactorily.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:mpopst:v:12:y:2005:i:1:p:17-38
    DOI: 10.1080/08898480590902145
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    References listed on IDEAS

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    1. J Bates & I Bracken, 1982. "Estimation of Migration Profiles in England and Wales," Environment and Planning A, , vol. 14(7), pages 889-900, July.
    2. 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.
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    Cited by:

    1. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    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. Ashira Menashe‐Oren & Philippe Bocquier, 2021. "Urbanization Is No Longer Driven by Migration in Low‐ and Middle‐Income Countries (1985–2015)," Population and Development Review, The Population Council, Inc., vol. 47(3), pages 639-663, September.
    4. Hyndman, Rob J. & Booth, Heather, 2008. "Stochastic population forecasts using functional data models for mortality, fertility and migration," International Journal of Forecasting, Elsevier, vol. 24(3), pages 323-342.
    5. David Plane, 2012. "What about aging in regional science?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(2), pages 469-483, April.
    6. Menashe-Oren, A. & Stecklov, G., 2017. "IFAD RESEARCH SERIES 17 - Population age structure and sex composition in sub-Saharan Africa: a rural-urban perspective," IFAD Research Series 280055, International Fund for Agricultural Development (IFAD).

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