Automation and income inequality in Europe

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Date:
2023-10-10
Authors:
Karina Doorley
Jan Gromadzki
Piotr Lewandowski
Dora Tuda
Philippe Van Kerm
Publication year:
2023
Publishing series:
IBS Working Paper
Publishing number:
6/2023
Publications category:
Abstract:

We study the effects of robot penetration on household income inequality in 14 European countries between 2006-2018, a period of rapid adoption of industrial robots. Automation reduced relative hourly wages and employment of more exposed demographic groups, similarly to the results for the US. Using robot-driven wage and employment shocks as input to the EUROMOD microsimulation model, we find that automation had minor effects on income inequality. Household labour income diversification and tax and welfare policies largely absorbed labour market shocks caused by automation. Transfers played a key role in cushioning the transmission of these shocks to household incomes.

Additional information:

We thank Karol Madoń for excellent research assistance. We thank Mikkel Barslund, Sydnee Caldwell, David Card, Cristiano Perugini, Vegard Skirbekk, and participants of the EALE Annual Conference 2023, ECINEQ Annual Meeting 2023, IEA Annual Meeting 2023, SOLE Annual Meeting 2023, TASKS VI conference, Untangled 2022 conference, VALURED 2024 workshop, and workshops in Oslo, Warsaw, and Trento for their comments. This paper uses Eurostat data. Eurostat has no responsibility for the results and the conclusions, which are those of the authors. The results presented here are based on EUROMOD version I3.86. Originally maintained, developed and managed by the Institute for Social and Economic Research (ISER), since 2021 EUROMOD is maintained, developed and managed by the Joint Research Centre (JRC) of the European Commission, in collaboration with Eurostat and national teams from the EU countries. We are indebted to the many people who have contributed to the development of EUROMOD. The results and their interpretation are the authors’ responsibility. This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No.~1001004776. Gromadzki acknowledges funding from the Polish-U.S. Fulbright Commission.

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