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Smoothing internal migration age profiles for comparative research

Author

Listed:
  • Aude Bernard

    (University of Queensland)

  • Martin Bell

    (University of Queensland)

Abstract

Background: Age patterns are a key dimension to compare migration between countries and over time. Comparative metrics can be reliably computed only if data capture the underlying age distribution of migration. Model schedules, the prevailing smoothing method, fit a composite exponential function, but are sensitive to function selection and initial parameter setting. Although non-parametric alternatives exist, their performance is yet to be established. Objective: We compare cubic splines and kernel regressions against model schedules by assessing which method provides an accurate representation of the age profile and best performs on metrics for comparing aggregate age patterns. Methods: We use full population microdata for Chile to perform 1,000 Monte-Carlo simulations for nine sample sizes and two spatial scales. We use residual and graphic analysis to assess model performance on the age and intensity at which migration peaks and the evolution of migration age patterns. Results: Model schedules generate a better fit when (1) the expected distribution of the age profile is known a priori, (2) the pre-determined shape of the model schedule adequately describes the true age distribution, and (3) the component curves and initial parameter values can be correctly set. When any of these conditions is not met, kernel regressions and cubic splines offer more reliable alternatives. Conclusions: Smoothing models should be selected according to research aims, age profile characteristics, and sample size. Kernel regressions and cubic splines enable a precise representation of aggregate migration age profiles for most sample sizes, without requiring parameter setting or imposing a pre-determined distribution, and therefore facilitate objective comparison.

Suggested Citation

  • 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.
    • Handle: RePEc:dem:demres:v:32:y:2015:i:33
    DOI: 10.4054/DemRes.2015.32.33
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    References listed on IDEAS

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    Cited by:

    1. Sigurd Dyrting & Andrew Taylor & Tom Wilson, 2024. "Application of P-TOPALS for Smoothing Input Data for Population Projections ‘At the Edge’," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 43(2), pages 1-28, April.
    2. Aude Bernard & Alina Pelikh, 2019. "Distinguishing tempo and ageing effects in migration," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(44), pages 1291-1322.
    3. Sigurd Dyrting & Andrew Taylor, 2021. "Smoothing destination-specific migration flows," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(2), pages 359-383, October.
    4. Philip Rees & Tom Wilson, 2023. "Accuracy of Local Authority Population Forecasts Produced by a New Minimal Data Model: A Case Study of England," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(6), pages 1-30, December.
    5. Sen Li & Jianfa Shen, 2024. "Dynamics of Intercity Migration Propensity in China: Evidence from an Age-Period-Cohort Analysis," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 43(5), pages 1-24, October.
    6. Aude Bernard & Francisco Rowe & Martin Bell & Philipp Ueffing & Elin Charles-Edwards, 2017. "Comparing internal migration across the countries of Latin America: A multidimensional approach," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-24, March.
    7. Aude Bernard & Martin Bell, 2018. "Internal migration and education: A cross-national comparison," Papers 1812.08913, arXiv.org.
    8. Aude Bernard & Martin Bell & Elin Charles-Edwards, 2016. "Internal migration age patterns and the transition to adulthood: Australia and Great Britain compared," Journal of Population Research, Springer, vol. 33(2), pages 123-146, June.
    9. Sigurd Dyrting, 2020. "Smoothing migration intensities with P-TOPALS," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 43(55), pages 1607-1650.

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    More about this item

    Keywords

    model migration schedule; cross-national comparison; migration age profile; kernel regression; cubic spline; smoothing;
    All these keywords.

    JEL classification:

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

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