Are machines stealing our jobs?

被引：26

作者：

Gentili, Andrea ^{[1
]}

Compagnucci, Fabiano ^{[2
]}

Gallegati, Mauro ^{[3
]}

Valentini, Enzo ^{[4
]}

机构：

[1] Univ Int Roma, Fac Econ, Via Cristoforo Colombo 200, I-00147 Rome, Italy

[2] Gran Sasso Sci Inst, Social Sci, Via Michele Iacobucci 2, I-67100 Laquila, Italy

[3] Univ Politecn Marche, Dept Management, Piazzale Martelli 8, I-60129 Ancona, Italy

[4] Univ Macerata, Dept Polit Sci Commun & Int Relat, Via Don Minzoni 2, I-62100 Macerata, Italy

来源：

CAMBRIDGE JOURNAL OF REGIONS ECONOMY AND SOCIETY | 2020年 / 13卷 / 01期

关键词：

robotisation; labour dislocation; cluster analysis; TECHNOLOGICAL-CHANGE; GROWTH; EMPLOYMENT; LABOR; PRODUCTIVITY; COUNTRIES; POLARIZATION; AUTOMATION; INEQUALITY; FUTURE;

D O I：

10.1093/cjres/rsz025

中图分类号：

F0 [经济学]; F1 [世界各国经济概况、经济史、经济地理]; C [社会科学总论];

学科分类号：

0201 ; 020105 ; 03 ; 0303 ;

摘要：

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.

引用

页码：153 / 173

页数：21

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