Digital Twins and Network Resilience in the EU ETS: Analysing Structural Shifts in Carbon Trading

Cláudia R. R. Eirado, Douglas Silveira and Daniel O. Cajueiro ()
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Cláudia R. R. Eirado: Department of Economics, University of Brasília (UnB), Brasília 70910-900, Brazil
Daniel O. Cajueiro: Department of Economics, University of Brasília (UnB), Brasília 70910-900, Brazil

Sustainability, 2025, vol. 17, issue 15, 1-31

Abstract: The European Union Emissions Trading System (EU ETS) and its underlying market structure play a central role in the EU’s climate policy. This study analyses how the network of trading relationships within the EU ETS has evolved from a hub-dominated architecture to one marked by structural change and the emergence of new trading dynamics. Using transaction data from Phases I–IV, we apply complex network analysis to assess changes in connectivity, centrality, and community structure. We then construct a Digital Twin of the EU ETS, integrating graph neural networks and logistic regression models to simulate the entry of new participants and predict future trading links. The results indicate shifts in network composition and connectivity, especially in Phase IV, where regulatory innovations and institutional mechanisms appear to play a key role. While our analysis focuses on structural dynamics, these patterns may have broader implications for market performance and policy effectiveness. These findings underscore the importance of monitoring the evolving trading network alongside price signals to support a resilient, efficient, and environmentally credible carbon market.

Keywords: digital twins; complex networks; Machine Learning; emissions trading; market structure; regulatory impacts (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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