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

TL;DR

This paper uses a GNN framework to analyze how the EU's CBAM policy impacts electricity prices and carbon intensity across European countries, revealing structural market shifts and competitive advantages.

Contribution

It introduces a novel spatio-temporal GNN approach to model cross-border spillover effects of CBAM on electricity markets, capturing complex structural impacts.

Findings

CBAM creates structural differences in the market.

Low-carbon countries may see price reductions.

High-carbon countries face increased costs.

Abstract

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.