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Modeling European Electricity Market Integration during turbulent times

Francesco Ravazzolo, Luca Rossini, Andrea Viselli

arXiv 29 Jun 2025 · Econometrics

arXiv:2506.23289 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper introduces a novel Bayesian reverse unrestricted mixed-frequency model applied to a panel of nine European electricity markets. Our model analyzes the impact of daily fossil fuel prices and hourly renewable energy generation on hourly electricity prices, employing a hierarchical structure to capture cross-country interdependencies and idiosyncratic factors. The inclusion of random effects demonstrates that electricity market integration both mitigates and amplifies shocks. Our results highlight that while renewable energy sources consistently reduce electricity prices across all countries, gas prices remain a dominant driver of cross-country electricity price disparities and instability. This finding underscores the critical importance of energy diversification, above all on renewable energy sources, and coordinated fossil fuel supply strategies for bolstering European energy security.

Citation extraction

38
references
74
in-text mentions
38
distinct cited
1
self-citations
10,706
main-text words

appendix boundary found by appendix_command · 88% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Gianfreda, A., F. Ravazzolo, and L. Rossini (2020) Comparing the forecasting performances of linear models for electricity prices with high RES penetration1.00053100%
2Casarin, R., C. Foroni, M. Marcellino, and F. Ravazzolo (2018) Uncertainty through the lenses of a mixed-frequency Bayesian panel Markov-switching model0.9507386%
3Canova, F. and M. Ciccarelli (2009) Estimating multicountry VAR models0.87472100%
4EU Agency for the Cooperation of Energy Regulators (2023, December) (2023) Demand response and other distributed energy resources: what barriers are holding them back? 2023 Market Monitoring Report0.81142100%
5International Energy Agency (2024) Analysis and forecast to 20260.81142100%
6Ravazzolo, F. and L. Rossini (2025) Is the Price Cap for Gas Useful? Evidence from European Countries self0.73732100%
7Oxford Institute for Energy studies (2024, October) (2024) Quarterly gas market review: Asia market drives price recovery0.64441100%
8Foroni, C., P. Guérin, and M. Marcellino (2018) Using low frequency information for predicting high frequency variables0.64422100%
9Gianfreda, A., F. Ravazzolo, and L. Rossini (2023) Large Time-Varying Volatility Models for Hourly Electricity Prices0.64422100%
10Hidalgo-Pérez, M., N. Collado, J. Galindo, and R. Mateo (2024) The Iberian exception: Estimating the impact of a cap on gas prices for electricity generation on consumer prices and market dyn…0.64422100%

Showing the top 10 of 38 scored citations.