Article (Scientific journals)
Foreign Workers and the Wage Distribution: What Does the Influence Function Reveal?
Choe, Chung; Van Kerm, Philippe
2018In Econometrics, 6 (3)
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Keywords :
immigrant wages; wage inequality; RIF regression; influence functions; cross-border workers; Luxembourg
Abstract :
[en] This paper draws upon influence function regression methods to determine where foreign workers stand in the distribution of private sector wages in Luxembourg, and assess whether and how much their wages contribute to wage inequality. This is quantified by measuring the effect that a marginal increase in the proportion of foreign workers—foreign residents or cross-border workers—would have on selected quantiles and measures of inequality. Analysis of the 2006 Structure of Earnings Survey reveals that foreign workers have generally lower wages than natives and therefore tend to haul the overall wage distribution downwards. Yet, their influence on wage inequality reveals small and negative. All impacts are further muted when accounting for human capital and, especially, job characteristics. Not observing any large positive inequality contribution on the Luxembourg labour market is a striking result given the sheer size of the foreign workforce and its polarization at both ends of the skill distribution.
Disciplines :
Quantitative methods in economics & management
Author, co-author :
Choe, Chung;  Hanyang University, Ansan, South Korea
Van Kerm, Philippe  ;  University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Integrative Research Unit: Social and Individual Development (INSIDE) ; Luxembourg Institute of Socio-Economic Research - LISER
External co-authors :
yes
Language :
English
Title :
Foreign Workers and the Wage Distribution: What Does the Influence Function Reveal?
Publication date :
September 2018
Journal title :
Econometrics
ISSN :
2225-1146
Publisher :
MDPI AG, Basel, Switzerland
Special issue title :
Econometrics and Income Inequality
Volume :
6
Issue :
3
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Computational Sciences
Funders :
FNR - Fonds National de la Recherche [LU]
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since 26 October 2018

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