Evaluating the effects of industrial robots on the European labour market : employment and wage effects

Abstract

While the nature of work and skill demand has changed multiple times, the pace of the change has accelerated significantly in a way never seen before. An amount of literature explains this by the technological advances that have occurred during the past decades. Increase in automation of tasks today is accompanied by concern of the future of jobs and wages. As machines are becoming smarter and can increasingly substitute human labor in tasks that require skills previously proven challenging to codify and automate, the spectrum of jobs with labor tasks amenable to automation is increasing. While there is a large body of literature investigating the impact of technological change on labor markets, there exists yet little empirical evidence on the impact of robot adoption in particular. Increased use of industrial robots appears to follow an inverse pattern as the decrease in hours worked and employment during the last two decades in parts of Europe. The purpose of the thesis is to evaluate the effects of industrial robots on the European labor landscape, analyzing the impact of increased robot adoption on hours worked and wages over time across industries in Europe. The analysis is based on the use of a novel panel data on robot adoption within 15 industries in 18 countries from 1995 to 2015. My findings suggest there is a negative correlation between the increased use of robots and the fall in hours worked. However, the impact of increased robot adoption on overall hours worked, employment, and wages remains ambiguous, as the results cannot be validated through statistical significance. I find however, that robot adoption has had a positive impact on low skilled workers, by increasing their labor shares. Though only marginally statistically significant, results are negative for both high skilled and middle skilled workers, across five aggregate sectors in 12 of the European countries included in the sample.