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Determinants and dynamics of migration to OECD countries in a three-dimensional panel framework

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  • Ilse Ruyssen
  • Gerdie Everaert
  • Glenn Rayp

Abstract

This paper investigates the determinants of bilateral immigrant flows to 19 OECD countries between 1998 and 2007 from both advanced and developing origin countries. We pay particular attention to dynamics by including both the lagged migrant flow and the migrant stock to capture partial adjustment and network effects. To correct for the dynamic panel data bias of the fixed effects estimator we use a bootstrap algorithm. Our results indicate that immigrants are primarily attracted by better income opportunities and higher growth rates abroad. Also short-run increases in the host country’s employment rate positively affect migration from both advanced and developing countries. High public services, on the other hand, discourage migration from advanced countries but exert a pull on migration from developing sources, in line with the welfare state hypothesis. Finally, we find evidence for both partial adjustment and the presence of strong network effects. This confirms that both should be considered as crucial elements of the migration model and that a correction for their joint inclusion is required. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Ilse Ruyssen & Gerdie Everaert & Glenn Rayp, 2014. "Determinants and dynamics of migration to OECD countries in a three-dimensional panel framework," Empirical Economics, Springer, vol. 46(1), pages 175-197, February.
  • Handle: RePEc:spr:empeco:v:46:y:2014:i:1:p:175-197
    DOI: 10.1007/s00181-012-0674-1
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    Cited by:

    1. Tilman Brück & Kai M. Dunker & Neil T. N. Ferguson & Aline Meysonnat & Eleonora Nillesen, 2018. "Determinants and Dynamics of Forced Migration to Europe: Evidence from a 3-D Model of Flows and Stocks," HiCN Working Papers 277, Households in Conflict Network.
    2. Hubert Jayet & Glenn Rayp & Ilse Ruyssen & Nadiya Ukrayinchuk, 2016. "Immigrants’ location choice in Belgium," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(1), pages 63-89, July.
    3. Amelia Aburn & Dennis Wesselbaum, 2017. "Gone with the Wind: International Migration," Working Papers 1708, University of Otago, Department of Economics, revised Apr 2017.
    4. Timo Mitze, 2019. "The migration response to local labour market shocks: Evidence from EU regions during the global economic crisis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(2), pages 271-298, April.
    5. Fullerton, Thomas M., Jr. & Walke, Adam G. & Villavicencio, Diana, 2015. "An Econometric Approach for Modeling Population Change in Doña Ana County, New Mexico," MPRA Paper 71141, University Library of Munich, Germany, revised 28 Jan 2015.
    6. Brück, Tilman & Dunker, Kai M. & Ferguson, Neil T.N. & Meysonnat, Aline & Nillesen, Eleonora, 2018. "Determinants and Dynamics of Forced Migration to Europe: Evidence from a 3-D Model of Flows and Stocks," IZA Discussion Papers 11834, Institute of Labor Economics (IZA).
    7. Andreas Backhaus & Inmaculada Martinez-Zarzoso & Chris Muris, 2015. "Do climate variations explain bilateral migration? A gravity model analysis," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-15, December.
    8. Rayp, Glenn & Ruyssen, Ilse & Standaert, Samuel, 2017. "Measuring and Explaining Cross-Country Immigration Policies," World Development, Elsevier, vol. 95(C), pages 141-163.
    9. Mohammad Reza Farzanegan & Hassan F. Gholipour & Mostafa Javadian, 2023. "Air pollution and internal migration: evidence from an Iranian household survey," Empirical Economics, Springer, vol. 64(1), pages 223-247, January.
    10. Robert Lehmann & Wolfgang Nagl, 2019. "Explaining spatial patterns of foreign employment in Germany," Regional Studies, Taylor & Francis Journals, vol. 53(7), pages 991-1003, July.
    11. Opolska, Iweta, 2017. "The efficacy of liberalization and privatization in introducing competition into European natural gas markets," Utilities Policy, Elsevier, vol. 48(C), pages 12-21.

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    More about this item

    Keywords

    International migration; Network effects; Dynamic panel data model; Bias correction; F22; J61; C33;
    All these keywords.

    JEL classification:

    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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