IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v43y2020i55.html
   My bibliography  Save this article

Smoothing migration intensities with P-TOPALS

Author

Listed:
  • Sigurd Dyrting

    (Charles Darwin University)

Abstract

Background: Age-specific migration intensities often display irregularities that need to be removed by graduation, but two current methods for doing so, parametric model migration schedules and non-parametric kernel regression, have their limitations. Objective: This paper introduces P-TOPALS, a relational method for smoothing migration data that combines both parametric and non-parametric approaches. Methods: I adapt de Beer’s TOPALS framework to migration data and combine it with penalized splines to give a method that frees the user from choosing the optimal number and position of knots and that can be solved using linear techniques. I compare this method to smoothing by model migration schedules and kernel regression using one-year and five-year migration probabilities calculated from Australian census data. Results: I find that P-TOPALS combines the strengths of both student model migration schedules and kernel regression to allow a good estimation of the high-curvature portion of the curve at young adult ages as well as a sensitive modelling of intensities beyond the labour force peak. Conclusions: P-TOPALS is a useful framework for incorporating non-parametric elements to improve a model migration schedule fit. It is flexible enough to capture the variety of profiles seen for both interstate and regional migration flows and is naturally suited to small populations where observed probabilities can be highly irregular from one age to the next. Contribution: I demonstrate a new method for migration graduation that brings together the strengths of both parametric and non-parametric approaches to give a good general-purpose smoother. An implementation of the method is available as an Excel add-in.

Suggested Citation

  • 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.
    • Handle: RePEc:dem:demres:v:43:y:2020:i:55
    DOI: 10.4054/DemRes.2020.43.55
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol43/55/43-55.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4054/DemRes.2020.43.55?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Tom Wilson, 2010. "Model migration schedules incorporating student migration peaks," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 23(8), pages 191-222.
    2. Joop de Beer, 2011. "A new relational method for smoothing and projecting age-specific fertility rates: TOPALS," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 24(18), pages 409-454.
    3. 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.
    4. Joop de Beer, 2012. "Smoothing and projecting age-specific probabilities of death by TOPALS," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 27(20), pages 543-592.
    5. Aude Bernard & Martin Bell & Elin Charles-Edwards, 2014. "Life-Course Transitions and the Age Profile of Internal Migration," Population and Development Review, The Population Council, Inc., vol. 40(2), pages 213-239, June.
    6. M. Bell & M. Blake & P. Boyle & O. Duke‐Williams & P. Rees & J. Stillwell & G. Hugo, 2002. "Cross‐national comparison of internal migration: issues and measures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(3), pages 435-464, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ameer Dharamshi & Magali Barbieri & Monica Alexander & Celeste Winant, 2025. "Jointly estimating subnational mortality for multiple populations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 52(3), pages 71-110.
    2. 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.
    3. Tom Wilson & Irina Grossman & Monica Alexander & Phil Rees & Jeromey Temple, 2022. "Methods for Small Area Population Forecasts: State-of-the-Art and Research Needs," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(3), pages 865-898, June.
    4. Sigurd Dyrting & Abraham Flaxman & Ethan Sharygin, 2022. "Reconstruction of age distributions from differentially private census data," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(6), pages 2311-2329, December.
    5. 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.
    6. Jan Weymeirsch & Julian Ernst & Ralf Münnich, 2024. "Model Recalibration for Regional Bias Reduction in Dynamic Microsimulations," Mathematics, MDPI, vol. 12(10), pages 1-25, May.
    7. Agnieszka Orwat-Acedańska, 2024. "Accuracy of small area mortality prediction methods: evidence from Poland," Journal of Population Research, Springer, vol. 41(1), pages 1-20, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aude Bernard & Martin Bell, 2018. "Internal migration and education: A cross-national comparison," Papers 1812.08913, arXiv.org.
    2. 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.
    3. 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.
    4. Jack DeWaard & Janna Johnson & Stephan Whitaker, 2019. "Internal migration in the United States: A comprehensive comparative assessment of the Consumer Credit Panel," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(33), pages 953-1006.
    5. Nico Keilman, 2023. "Can We Rely on Projections of the Immigrant Population? The Case of Norway," European Journal of Population, Springer;European Association for Population Studies, vol. 39(1), pages 1-26, December.
    6. Sigurd Dyrting & Abraham Flaxman & Ethan Sharygin, 2022. "Reconstruction of age distributions from differentially private census data," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(6), pages 2311-2329, December.
    7. 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.
    8. 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.
    9. 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.
    10. Keilman, Nico, 2016. "Household forecasting: Preservation of age patterns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 726-735.
    11. 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.
    12. 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.
    13. Aude Bernard, 2017. "Cohort Measures of Internal Migration: Understanding Long-Term Trends," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2201-2221, December.
    14. 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.
    15. repec:osf:osfxxx:y9ke4_v1 is not listed on IDEAS
    16. Saavedra Facusse,Trinidad Berenice & Inchauste Comboni,Maria Gabriela, 2023. "Why Do People Move across State Borders ? Evidence from Mexico," Policy Research Working Paper Series 10493, The World Bank.
    17. Biavaschi, Costanza & Facchini, Giovanni, 2020. "Immigrant Franchise and Immigration Policy: Evidence from the Progressive Era," IZA Discussion Papers 13195, Institute of Labor Economics (IZA).
    18. Antoine Grandclement & Guilhem Boulay, 2021. "From The Uneven De-Diversification Of Local Financial Resources To Planning Policies: The Residentialization Hypothesis," Post-Print halshs-03322259, HAL.
    19. Sunganani V. Kalemba & Aude Bernard & Jonathan Corcoran & Elin Charles-Edwards, 2022. "Has the decline in the intensity of internal migration been accompanied by changes in reasons for migration?," Journal of Population Research, Springer, vol. 39(3), pages 279-313, September.
    20. Tom Wilson & Irina Grossman & Monica Alexander & Phil Rees & Jeromey Temple, 2022. "Methods for Small Area Population Forecasts: State-of-the-Art and Research Needs," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(3), pages 865-898, June.
    21. Liubov Antosik & Natalya Ivashina, 2019. "Modeling of spatial dependence in the migration flows of graduates of the higher education institutions of the Russian Federation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 54, pages 70-89.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:dem:demres:v:43:y:2020:i:55. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Editorial Office (email available below). General contact details of provider: https://www.demogr.mpg.de/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.