Market power abuse in wholesale electricity markets

2025-06-04

AI Summary

This paper investigates the dynamic relationship between generators’ hedging behavior and market power abuse in wholesale electricity markets. Using hourly unit-level data from Germany (2019–2024), we develop the first hedging-driven, hourly market power incentive quantification framework, isolating supply distortions—capacity withholding and push-in—that are strictly driven by economic incentives and thereby mitigating unobserved cost bias. Employing microeconometric analysis and a causal identification design based on continuous variation in incentive intensity, we find that each additional euro of net hedging gain increases the probability of capacity withholding by 1% and push-in by 0.3%. These results provide robust empirical evidence that financial hedging induces systemic market power abuse, revealing a novel mechanism through which long-term financial contracts may erode spot market competitiveness and efficiency.

Technology Category

• Game Theory and Economic Paradigms: Auctions and Market-Based Systems
• Multiagent Systems: Mechanism Design
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Security and Privacy: Large-scale security measurements
• Responsible Web: Measurement, analysis, and circumvention of Web censorship

Abstract

In wholesale electricity markets, prices fluctuate widely from hour to hour and electricity generators price-hedge their output using longer-term contracts, such as monthly base futures. Consequently, the incentives they face to drive up the power prices by reducing supply has a high hourly specificity, and because of hedging, they regularly also face an incentive to depress prices by inflating supply. In this study, we explain the dynamics between hedging and market power abuse in wholesale electricity markets and use this framework to identify market power abuse in real markets. We estimate the hourly economic incentives to deviate from competitive behavior and examine the empirical association between such incentives and observed generation patterns. Exploiting hourly variation also controls for potential estimation bias that do not correlate with economic incentives at the hourly level, such as unobserved cost factors. Using data of individual generation units in Germany in a six-year period 2019-2024, we find that in hours where it is more profitable to inflate prices, companies indeed tend to withhold capacity. We find that the probability of a generation unit being withheld increases by about 1 % per euro increase in the net profit from withholding one megawatt of capacity. The opposite is also true for hours in which companies benefit financially from lower prices, where we find units being more likely to be pushed into the market by 0.3 % per euro increase in the net profit from capacity push-in. We interpret the result as empirical evidence of systematic market power abuse.

Problem

• Analyzing market power abuse dynamics in wholesale electricity markets
• Estimating hourly incentives for competitive behavior deviation
• Identifying empirical evidence of systematic market manipulation

Innovation

• Estimates hourly economic incentives for deviations
• Links incentives to observed generation patterns
• Uses hourly data to control estimation bias