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Selecting only the best and brightest? An assessment of migration policy selectivity and its effectiveness

Published online by Cambridge University Press:  18 September 2024

Glenn Rayp ,
Ilse Ruyssen Open the ORCID record for Ilse Ruyssen [Opens in a new window]  and
Samuel Standaert
Glenn Rayp
Affiliation:
Department of Economics, Ghent University, Ghent, Belgium
Ilse Ruyssen*
Affiliation:
UNU-CRIS, Bruges, Belgium
Samuel Standaert
Affiliation:
Department of Economics, Ghent University, Ghent, Belgium
*
Corresponding author: Ilse Ruyssen; Email: [email protected]
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Abstract

This paper introduces a new set of comprehensive and cross-country-comparable indexes of migration policy selectivity. Crucially, these reflect the multidimensional nature of the differential treatment of migrants. We use these indexes to study the evolution of migration policy selectivity and estimate how they affect migration flows. Combining all publicly available and relevant data since WWII, we build three composite indexes that identify selectivity in terms of skills, economic resources and nationality. First, we use these to characterize migration policies in 42 countries between 1990 and 2014. Second, we examine the relationship between the selectivity of migration policy and migration flows. Each of the three dimensions of migration policy is found to correlate strongly and significantly with both the size and structure of migration flows.

Keywords

Effectivenessinternational migrationmigration policyselectivity

JEL classification

C43: Index Numbers and Aggregation C32: Time-Series Models • Dynamic Quantile Regressions • Dynamic Treatment Effect Models • Diffusion Processes • State Space Models P16: Political Economy F22: International Migration
Type
Research Paper
Information
Journal of Demographic Economics , Volume 90 , Special Issue 3: Migration and Development , September 2024 , pp. 352 - 383
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press in association with Université catholique de Louvain

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