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This paper investigates the impact of the EU's Carbon Border Adjustment Mechanism (CBAM) on European electricity prices using a spatio-temporal Graph Neural Network (GNN) framework to model cross-border spillover effects. The GNN models electricity prices and carbon intensity across eight European countries, revealing that CBAM acts as a market transformer rather than a uniform tax. Results indicate that low-carbon countries may see decreased electricity prices due to a competitive advantage, while high-carbon countries face increased costs due to a shift in the market's merit order.
CBAM could reshape Europe's electricity market, giving low-carbon countries a competitive edge while burdening high-carbon economies.
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.
