Industrial robotics have become a pivotal part of manufacturing, aiming to increase productivity, reduce costs, and improve quality. This thesis examines the impact of industrial robotics on EU economies by investigating the relationship between robotic adoption and macroeconomic indicators, including GDP per capita and the unemployment rate. The study uses a panel dataset, which covers EU member states over the past two decades. Using regression and time-series analyses, I have built a fixed-effects multiple regression model and an autoregressive distributed lag model, respectively. The research results verify the hypotheses of positive relationships of robotic installations with GDP per capita, and the unemployment rate. Findings suggest a significant positive and long-term impact between robotics and economic growth, with evidence of wide deployment in various industries, including automotive, electronics, logistics, and more. However, the analysis reveals a negative short-term impact on employment, which can be explained by job displacement and new skill requirements after technology-driven structural changes in manufacturing and production processes.
The impact of industrial robotics on macroeconomic indicators goes beyond the theoretical and practical implications. Such automation technologies shape the economies of the EU, and this study contributes to understand the extent of the impact by providing insights for policymakers and industry stakeholders.