Are machines stealing our jobs?

Publication Type:

Journal Article

Authors:

Gentili, Andrea; Compagnucci, Fabiano; Gallegati, Mauro; Valentini, Enzo

Source:

Cambridge Journal of Regions, Economy and Society, Volume 13, Number 1, p.153–173 (2020)

Keywords:

cluster analysis, e24, e66, j24, jel classifications, labour dislocation, robotisation

Abstract:

This study aims to contribute empirical evidence to the debate about the future of work in an increasingly robotised world. We implement a data-driven approach to study the technological transition in six leading Organisation for Economic Co-operation and Development (OECD) countries. First, we perform a cross-country and cross-sector cluster analysis based on the OECD-STAN database. Second, using the International Federation of Robotics database, we bridge these results with those regarding the sectoral density of robots. We show that the process of robotisation is industry- and country-sensitive. In the future, participants in the political and academic debate may be split into optimists and pessimists regarding the future of human labour; however, the two stances may not be contradictory.