Enhancing EU Policy Through Complexity Metrics: A New Lens for Research and Innovation

Abstract

In a knowledge-based economy, understanding local capabilities is essential for identifying regional specialisations and technological trajectories. Recognizing where valuable knowledge resides and how innovation systems evolve is vital for enhancing the European Union’s competitiveness and overcoming some of the multifaceted challenges the world is facing today. From a policy perspective, this understanding is a crucial input for research and innovation (R&I) policies. Effective R&I policies require data-driven decisions based on comprehensive analysis. However, traditional indicators tend to miss the necessary nuances of technological progress by focusing on the quantity instead of quality of knowledge output. This has prompted a growing interest in complementary quality-based metrics, including the concepts of complexity and relatedness. Complexity captures the diversity and interdependencies of economic activities, while relatedness measures the connections between different economic activities. This paper explains how incorporating these metrics can enhance the ability of the EU to foster economic growth and address societal challenges through the design of more impactful policies. In particular, the paper focuses on how these metrics can inform three EU policy priorities: safeguarding access to critical technologies, fostering the green transition and promoting greater territorial cohesion.