Language Skills and Labor Market Performance of Immigrants in the Netherlands

Yuxin Yao () and Jan van Ours
Additional contact information
Yuxin Yao: Tilburg University

No 1505, RF Berlin - CReAM Discussion Paper Series from Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM)

Abstract: Many immigrants in the Netherlands have poor Dutch language skills. They face problems in speaking and reading Dutch. Our paper investigates how these problems affect their labor market performance in terms of employment, hours of work and wages. We find that for female immigrants language problems have significantly negative effects on hourly wages but not on employment probability and hours of work. For male immigrants language problems do not affect employment probability, hours of work or hourly wages.

Keywords: Language skills; immigrants; labor market performance (search for similar items in EconPapers)
JEL-codes: J15 J24 (search for similar items in EconPapers)
Date: 2015-02
New Economics Papers: this item is included in nep-eur and nep-mig
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (59)

Downloads: (external link)
https://www.cream-migration.org/publ_uploads/CDP_05_15.pdf (application/pdf)

Related works:
Working Paper: Language Skills and Labor Market Performance of Immigrants in the Netherlands (2015)
Working Paper: Language Skills and Labor Market Performance of Immigrants in the Netherlands (2015)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:crm:wpaper:1505

Access Statistics for this paper

More papers in RF Berlin - CReAM Discussion Paper Series from Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM) Contact information at EDIRC.
Bibliographic data for series maintained by CReAM Administrator () and Matthew Nibloe ().