Technology and Skill Demand: Labor Market Polarization in European Countries
Martin Labaj and
Matej Vitalos
Additional contact information
Martin Labaj: University of Economics in Bratislava, Slovakia
Matej Vitalos: University of Economics in Bratislava, Slovakia
Czech Journal of Economics and Finance (Finance a uver), 2024, vol. 74, issue 2, 255-270
Abstract:
technological change. In particular, it studies the relationship between displacement and reinstatement effects associated with automation and new tasks on the one hand and the demand for skills on the other. The analysis focuses on a group of advanced European countries and provides robust empirical evidence that technological progress leads to labor market polarization, as the tasks created by new technologies seem to be more suitable for high- and low-skilled workers. In addition to this novel finding of the reinstatement-driven hollowing out of the middle class, we confirm that automation contributes to top-bottom inequality. We also document that men and women are disproportionately affected by displacement and reinstatement technologies, and show that the labor market polarization is strongly associated with middle-aged cohorts of workers.
Keywords: technological change; displacement; reinstatement; skill demand; labor market polarization (search for similar items in EconPapers)
JEL-codes: J23 J24 O33 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
https://journal.fsv.cuni.cz/mag/article/show/id/1534 (application/pdf)
Related works:
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:fau:fauart:v:74:y:2024:i:2:p:255-270
Access Statistics for this article
More articles in Czech Journal of Economics and Finance (Finance a uver) from Charles University Prague, Faculty of Social Sciences Contact information at EDIRC.
Bibliographic data for series maintained by Natalie Svarcova ().