Routine and non-routine sectors, tasks automation and wage polarization

Óscar Afonso and Rosa Forte

Applied Economics, 2024, vol. 56, issue 55, 7262-7285

Abstract: Recent and detailed data point to a polarization of wages with regard to the distribution of skills, particularly in developed countries over the past three decades, requiring the literature to address modelling approaches focused on automating different types of tasks. In the DTC literature, the technological-knowledge bias leads to an increase in the wage of skilled workers relative to unskilled workers. Motivated by this literature, this paper considers three types of workers (skilled, medium-skilled and unskilled) but retain the economic mechanisms that produce the results. Thus, wage inequality continues to result from the technological-knowledge bias, which, in the face of automation dynamics, reveals that medium-skilled workers are the relatively most penalized, generating wage polarization. Furthermore, as in the directed technical change literature, the relative supply of skilled workers continues to affect the skill premium.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2023.2280461 (text/html)
Access to full text is restricted to subscribers.

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:taf:applec:v:56:y:2024:i:55:p:7262-7285

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2023.2280461

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().