Understanding the European energy crisis through structural causal models

Fuente: arXiv
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Hauptverfasser: Tausendfreund, Anton, Schreyer, Sarah, Immig, Florian, Oberhofer, Ulrich, Trebbien, Julius, Praktiknjo, Aaron, Schäfer, Benjamin, Witthaut, Dirk
Format: Preprint
Veröffentlicht: 2025
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author Tausendfreund, Anton
Schreyer, Sarah
Immig, Florian
Oberhofer, Ulrich
Trebbien, Julius
Praktiknjo, Aaron
Schäfer, Benjamin
Witthaut, Dirk
author_facet Tausendfreund, Anton
Schreyer, Sarah
Immig, Florian
Oberhofer, Ulrich
Trebbien, Julius
Praktiknjo, Aaron
Schäfer, Benjamin
Witthaut, Dirk
contents Natural gas supplies in Europe were disrupted and energy prices soared in the context of Russia's invasion of Ukraine. Electricity prices in France experienced the largest relative increase among European countries, even though natural gas plays a negligible role in the French electricity system. In this article, we demonstrate the importance of causal statistical methods and propose causal graphs to investigate the French electricity market and pinpoint key influencing factors on electricity prices and net exports. We demonstrate that a causal approach resolves paradoxical results of simple correlation studies and enables a quantitative analysis of indirect causal effects. We introduce a linear structural causal model as well as non-linear tree-based machine learning combined with Shapley flows. The models elucidate the interplay of gas prices and the unavailability of nuclear power plants during the energy crisis: The high unavailability made France dependent on imports and linked prices to neighbouring countries.
format Preprint
id arxiv_https___arxiv_org_abs_2506_00680
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Understanding the European energy crisis through structural causal models
Tausendfreund, Anton
Schreyer, Sarah
Immig, Florian
Oberhofer, Ulrich
Trebbien, Julius
Praktiknjo, Aaron
Schäfer, Benjamin
Witthaut, Dirk
Applications
Natural gas supplies in Europe were disrupted and energy prices soared in the context of Russia's invasion of Ukraine. Electricity prices in France experienced the largest relative increase among European countries, even though natural gas plays a negligible role in the French electricity system. In this article, we demonstrate the importance of causal statistical methods and propose causal graphs to investigate the French electricity market and pinpoint key influencing factors on electricity prices and net exports. We demonstrate that a causal approach resolves paradoxical results of simple correlation studies and enables a quantitative analysis of indirect causal effects. We introduce a linear structural causal model as well as non-linear tree-based machine learning combined with Shapley flows. The models elucidate the interplay of gas prices and the unavailability of nuclear power plants during the energy crisis: The high unavailability made France dependent on imports and linked prices to neighbouring countries.
title Understanding the European energy crisis through structural causal models
topic Applications
url https://arxiv.org/abs/2506.00680