Project Untangled

Follow us on social media

Project Untangled



    European and national policymakers must take decisive action to ensure the economic boost generated by increased digital transformation is shared fairly across regions, sectors, and occupations, a new Project UNTANGLED study recommends.



    New results from UNTANGLED paints a nuanced picture of robotisation and automation’s effects, helping to ease concerns about conditions for millions of workers as technological innovations enhance efficiency and replace tasks. While impacts will be heterogeneous, approximately 80% of 100 major European economic areas will experience net benefits in average workers’ welfare.


    “Digital transformation represents more of an opportunity than a risk for most regions in Europe,” said Michal Burzynski, a labour market research scientist at the Luxembourg Institute of Socio-Economic Research (LISER), and a study co-author. “That said, workers in some parts of Europe will be negatively affected. Understanding these implications is crucial for formulating effective policies that address the challenges, and opportunities, arising from robotisation and automation.”


    To evaluate the potential consequences of robotisation and automation on European labour markets, the researchers used a general equilibrium model, combined with projection scenarios, to benchmark how future technological progress may reshape labour in Europe.


    With data on GDP, wages, employment, education and migration from Eurostat, OECD, and on robotisation and automation from IFR and EU-KLEMS, the researchers quantified average wage effects and changes in wage dispersion across occupations, sectors, geographical areas, and worker groups.


    Overall, the researchers determined that while a strong majority of regions benefit from robotisation and automation, the effect is heterogeneous, both across and within countries.


    “The Paris area, Austria, Switzerland, as well as Nordic and some Baltic regions belong to the main nominal GDP winners of robotisation and automation, followed by the rest of France, the south of Germany, Benelux, and Ireland,” they wrote. “A weaker positive or slightly negative impact is observed in the UK, and southern and eastern European regions.”


    With a benchmark scenario calculated, the researchers then analysed the potential effects of robotisation and automation on workers with different origins, education levels, and skills using three scenarios of robotisation and automation: slow, medium, and fast. The slow adoption scenario will reduce average native welfare in half of the Europen regions. In the medium adoption scenario, average native welfare improved across Europe, except for in roughly 20 regions, particularly in France and Poland. In the fast adoption scenario, the negative welfare impacts concern fewer regions.


    Across sectors, impacts on labour supply also varied. Manufacturing was projected as the most likely beneficiary of robotisation and automation in in Belgian and German regions. Public administration, education, and health services were projected to gain in most regions with higher positive impacts in Nordic and Alpine countries, while transport and storage was projected to experience the highest growth in eastern Europe and Austria. In contrast, construction and financial services tended to shrink in most regions.


    The disparity in regional and sectoral benefits demands strong policy responses, the researchers noted.


    “As robotisation and automation continue to progress, it’s increasingly probable that this trend will impact workers who have, thus far, been relatively unaffected,” said Joël Machado, a LISER research scientist and another study co-author. “Our projected scenarios can help policymakers better target interventions that support those who are adversely affected by the digital transformation.”


    Burzynski, M., Machado, J., and Martin, L. (2023). Digital transformation, demographic changes, and labour markets. Projected implications for 100 European regions (Deliverable 6.2). Leuven: UNTANGLED project 1001004776 – H2020.


    The paper is available here.

    2021 © UNTANGLED. All rights reserved.
    This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101004776

    Follow us on social media