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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2023

Autores

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

Revista

Título: Applied Economics

Páginas: 1-24

ISSN: 0003-6846

Editora: Taylor & Francis

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 24