, Volume 46, Issue 4, pp 669–690 | Cite as

English skills, labour market status and earnings of Turkish women

  • Antonio Di PaoloEmail author
  • Aysit Tansel
Original Paper


In this paper, we investigate the effect of the level of English skills on the labour market outcomes of Turkish women, using data from the Adult Education Survey of 2007. By adopting a bivariate equation framework, we jointly model the effect of English skills on labour market status and, conditional on being a wage earner, on monthly earnings and occupational status. The multinomial equation that explains labour market status allows for a different effect of language knowledge on the probability of being employed, unemployed but actively looking for a job, an unpaid family worker or involved in household tasks. The results indicate that being proficient in English is conditionally associated with a higher probability of being employed as a wage earner and, to a lesser extent, unemployed but looking for a job, whereas it decreases the likelihood of being involved in household tasks. Moreover, there is a significant conditional correlation between having a high level of skills in English and earnings, which is only modestly reduced when job-related variables and (especially) occupation dummies are included as additional controls. Indeed, being proficient in English barely affects occupational status when selection into employment status is controlled for. Therefore, the knowledge of foreign languages (in this case English) seems to stimulate labour market participation and earnings capacity, but does not substantially affect the occupational position of women in the Turkish labour market.


English skills Females Labour market status Earnings Occupation 

JEL Classification

J16 J24 J31 O15 Z13 



We would like to thank three anonymous referees of this journal for their insightful comments, which helped to improve the paper. Di Paolo gratefully acknowledges funding from the MEC Grant No. ECO2016-75805-R and the RecerCaixa Grant 2016ACUP00020.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.AQR-IREA, University of BarcelonaBarcelonaSpain
  2. 2.Middle East Technical University, ERF and IZAAnkaraTurkey

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