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Article
Publication date: 13 November 2009

Herbert Brücker and Cécily Defoort

The paper seeks to analyse the self‐selection of international migrants on observable skills.

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Abstract

Purpose

The paper seeks to analyse the self‐selection of international migrants on observable skills.

Design/methodology/approach

Based on an extended version of the Roy model, which considers random migration costs, the authors analyse the self‐selection of migrants on observable skills empirically. For this purpose, the authors employ a new panel data set on the educational attainment of migrants, which covers migration from 143 sending countries into the six main receiving countries in the OECD from 1975 to 2000.

Findings

Migrants tend to be positively self‐selected on observable skills, although the inequality in earnings is larger in the sending country relative to the destination countries. The estimation results indicate that a higher inequality in the distribution of earnings in both the receiving and the sending country affects the skill bias of the migrant population favourably. Moreover, higher migration costs and selective immigration policies increase the skill level of migrants relative to those of stayers in the sending countries.

Research limitations/implications

The results may be affected by measurement error, since it was necessary to approximate the returns to education by measures for the inequality of earnings.

Practical implications

The paper provides, inter alia, insights as to how immigration and other policies affect the self‐selection of migrants on observable skills, which may be relevant for policy makers.

Originality/value

To the authors' knowledge, this is the first paper to analyse the self‐selection of migrants on the basis of a panel data set.

Details

International Journal of Manpower, vol. 30 no. 7
Type: Research Article
ISSN: 0143-7720

Keywords

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Article
Publication date: 13 November 2009

Uwe Blien, Elke J. Jahn and Gesine Stephan

920

Abstract

Details

International Journal of Manpower, vol. 30 no. 7
Type: Research Article
ISSN: 0143-7720

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