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Modelling Asylum Migration Pull-Force Factors in the EU-15


  • Gerard Keogh

    (Trinity College Dublin)


We model the relationship between asylum applications across the EU-15 and three key pull-force factors, GDP, the recognition rate (grants of refugee status as a percentage of all refugee decisions) and refugee stocks. A Dynamic Coefficient Random Effects Panel model is employed which captures both the country specific variance and temporal features. This model provides deeper insight into the relationship than has hitherto been possible. We show for Austria, Spain and possibly Belgium that the three predictive factors dominate while for other countries in the EU-15 country specific factors are more important. In relation to temporal effects we show both GDP and the recognition rate at the overall EU-15 level remain significant over time but refugee stock does not. We also show a downward level shift occurred in the elasticity of recognition rate in 2002 resulting in fewer refugees being recognised (i.e., granted refugee status) and, therefore, providing evidence that asylum policies have become more restrictive.

Suggested Citation

  • Gerard Keogh, 2013. "Modelling Asylum Migration Pull-Force Factors in the EU-15," The Economic and Social Review, Economic and Social Studies, vol. 44(3), pages 371-399.
  • Handle: RePEc:eso:journl:v:44:y:2013:i:3:p:371-399

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    References listed on IDEAS

    1. Ralph Rotte & Michael Vogler, 2000. "The effects of development on migration: Theoretical issues and new empirical evidence," Journal of Population Economics, Springer;European Society for Population Economics, vol. 13(3), pages 485-508.
    2. Andrew C. Harvey, 1990. "The Econometric Analysis of Time Series, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026208189x, December.
    3. Anna Mayda, 2010. "International migration: a panel data analysis of the determinants of bilateral flows," Journal of Population Economics, Springer;European Society for Population Economics, vol. 23(4), pages 1249-1274, 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.
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    Cited by:

    1. Gerard Keogh, 2016. "Quantifying the Importance of Nationality in Determining International Protection Outcomes in Ireland," The Economic and Social Review, Economic and Social Studies, vol. 47(2), pages 247-270.
    2. Rossi, Enzo, 2017. "Superseding Dublin: The European asylum system as a non-cooperative game," International Review of Law and Economics, Elsevier, vol. 51(C), pages 50-59.
    3. Hannes Weber, 2018. "Higher acceptance rates of asylum seekers lead to slightly more asylum applications in the future," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 39(47), pages 1291-1304.

    More about this item


    migration; asylum seekers; European Union;


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