Automation and Labor Demand in European Countries: A Task-based Approach to Wage Bill Decomposition

Abstract

To understand the evolution of labor demand in European countries in the context of automation and other emerging technologies, we apply the decomposition developed by Acemoglu and Restrepo (2019) to European data. At the center of this framework is the task content of production-measuring the allocation of tasks to factors of production. By creating a displacement effect, automation shifts the task content of production against labor, while the introduction of new tasks in which labor has a comparative advantage increases the labor demand via the reinstatement effect. Contrary to the US experience, in a group of 10 European countries, the displacement effect of automation was completely counterbalanced by technologies that create new tasks in which labor has a comparative advantage. Furthermore, our crosscountry comparison reveals a substantial variation across countries. The cumulative change in the task content of production ranges from 6.2% in the United Kingdom to a strong negative effect, namely-7.6%, in Sweden. A part of the differences can be explained by the rate of adoption of industrial robots. We document a strong unconditional relationship between the change in robot density and the displacement effect. However, differences in the reinstatement effect remain unexplained.

Technology and jobs: A systematic literature review

“…The highest relative support (87%) for the replacement effect comes from studies on robots (n=13) (Acemoglu and Restrepo, 2019;Acemoglu and Restrepo, 2020;Blanas et al, 2019;Borjas and Freeman, 2019;Camina et al, 2020;Compagnucci et al, 2019;de Vries et al, 2020;Dodel and Mesch, 2020;Edler and Ribakova, 1994;Faber, 2020;Graetz and Michaels, 2018;Jung and Lim, 2020;Labaj and Vitaloš, 2020). Amongst these, Compagnucci et al (2019) reported a positive effect on wages which is outweighed by employment losses, yielding a net negative effect on the wage bill.…”

“…One macro-level robot study examined the impact of robots, measured by the number of robots per thousand workers, on changes in the country-level wage bill (Labaj and Vitaloš, 2020). The authors found evidence for the existence of the replacement effect, but simultaneously reported that negative employment effects are overcompensated by the reinstatement of new labor.…”

“…Nine reinstatement supporting studies analyzed the impact of Robots (Acemoglu and Restrepo, 2019;Blanas et al, 2019;de Vries et al, 2020;Dekle, 2020;Edler and Ribakova, 1994;Gentili et al, 2020;Graetz and Michaels, 2018;Labaj and Vitaloš, 2020;Leigh et al, 2019). Two thirds of them reported ambiguous effects on net employment and the remaining three (Dekle, 2020;Gentili et al, 2020;Leigh et al, 2019) found positive effects.…”

“…The effects are clustered in high-tech industries which account for a small share of total employment. Labaj and Vitaloš (2020) offer a macro-level regression analysis exploring how variations in the economy wide wage bill and labor share are explained by robot-diffusion rates in the US and Europe. They decomposed aggregate changes in the task content of production into a reinstatement and replacement effect and found evidence for both.…”