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

• Type: Article in International Scientific Journal
• Date: 2024-11-25

Authors

Óscar Afonso (Author) FEP; Rosa Maria Forte (Author) FEP

Journal

Title: Applied Economics

Vol. 56 No. 55

Pages: 7262-7285

ISSN: 0003-6846

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-00Z-HYT

DOI: 10.1080/00036846.2023.2280461

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 24