Automation and growth in the European Union: sectoral insights from robot density analysis
DOI: https://doi.org/10.3846/tede.2026.25244Abstract
This study explores the impact of robot density on economic performance across three key sectors in selected EU countries. While prior research has discussed the benefits and drawbacks of automation, few have empirically assessed its sector-specific effects on gross value added. Using panel data from Eurostat, the International Federation of Robotics (2024), and World Robotics, the paper applies the Method of Moments Quantile Regression (MMQR) to capture heterogeneous impacts across performance levels. Core variables include gross value added, real economic growth, R&D expenditure, and the number of specialists in scientific and technological fields. Results indicate that increased robot density significantly enhances value added, particularly in higher-performing sectors. The influence of R&D and human capital varies across sectors, highlighting the need for targeted policy design. The paper’s novelty lies in its differentiated, cross-sectoral approach, offering robust evidence on how and where robotics contributes to value creation. It advances the literature by integrating technological adoption with sectoral economic outcomes through advanced econometric techniques. Policymakers are encouraged to support automation through fiscal incentives, invest in reskilling programs, and develop innovation strategies tailored to specific sectors to foster inclusive and sustainable growth within the EU’s evolving economic landscape.
First published online 30 March 2026
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automation, sectoral performance, robot density, gross value added, industrial robotics, MMQRHow to Cite
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