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Will the Carbon Border Adjustment Mechanism Impact European Electricity Prices? A GNN-Based Network Analysis

arXiv 2605.03304 ↗First posted 5 May 2026cs.LG cs.CY cs.SYcited by 0

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Abstract (arXiv)

The European Union's Carbon Border Adjustment Mechanism (CBAM) creates a complex challenge for the interconnected European electricity market. Traditional static analyses often miss the cross-border spillover effects that are vital for understanding this policy. This paper addresses this gap by developing a spatio-temporal Graph Neural Network (GNN) framework. It quantifies how CBAM affects electricity prices and carbon intensity (CI) at the same time. We modeled a subgraph of eight European countries. Our results suggest that CBAM is not just a uniform tax. Instead, it acts as a tool that transforms the market and creates structural differences. In our simulated scenarios, we observe that low-carbon countries like France and Switzerland can gain a competitive advantage. This suggests a potential decrease in their domestic electricity prices. Meanwhile, high-carbon countries like Poland face a double burden of rising costs. We identify the primary driver as a fundamental shift in the market's merit order.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 16 references that are in the map. First posted on arXiv 5 May 2026.

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References · 2

  1. 2018How Powerful are Graph Neural Networks?cited by 4,393
  2. 2017An Overview of Multi-Task Learning in Deep Neural Networkscited by 803

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