PhD Position in Energy Market Dynamics: Spatial Competition, Regulation, and Society
Explore how physical and commercial constraints shape electricity market competition and integration.
Best for:Best for economists or social scientists with a strong quantitative background in econometrics, energy markets, or spatial analysis, interested in applied research at the intersection of regulation, technology, and market design.
Overview
This PhD position at Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU) focuses on analyzing energy market dynamics, particularly the role of spatial competition, grid constraints, and regulatory impacts on electricity trade. The project will develop novel network-weighted measures of competition, test the effectiveness of transmission networks, and simulate counterfactual scenarios (e.g., interconnector expansions or outages) to assess their impact on prices, congestion, and market integration. The research will leverage empirical data from EPEX SPOT and ENTSO-E, employing advanced econometric techniques like NARDL (Nonlinear Asymmetric Dynamic Linear Models) to account for uncertainty and asymmetric effects. The successful candidate will contribute to understanding how grid design and regulatory frameworks influence market efficiency and societal outcomes in the energy transition.
What you'll do
- Develop network-weighted measures of spatial competition in electricity markets, incorporating usable interconnection capacity, congestion, and transmission sensitivity.
- Extend competition measures to account for cross-zonal trading frictions, including persistent price spreads, congestion costs, and transmission capacity limits.
- Model firms and flexible demand competing across constrained transmission networks using computational and econometric techniques.
- Simulate counterfactual scenarios such as interconnector expansions, transmission outages, or alternative bidding-zone configurations to assess their impact on prices and market integration.
- Leverage EPEX SPOT day-ahead prices, ENTSO-E data, and other empirical sources to validate and refine analytical models.
- Apply NARDL (Nonlinear Asymmetric Dynamic Linear Models) to decompose changes in explanatory variables (e.g., neighboring prices, import capacity) into short-run and long-run effects.
- Conduct sensitivity analyses to account for uncertainty in capacity, network weights, and market-uncertainty measures (e.g., forecast errors for wind/solar/load).
- Publish findings in peer-reviewed journals and present results at academic conferences.
- Collaborate with energy market stakeholders to ensure policy-relevant insights.
Requirements
Degree required: Master's degree in Economics, Energy Systems, Applied Mathematics, or a related quantitative discipline
Degree offered: PhD
Language: English; proficiency sufficient for academic research and publication
Instruction: English
- Strong quantitative and econometric skills, particularly in time-series analysis and dynamic modeling (e.g., NARDL)
- Familiarity with energy market data (e.g., EPEX SPOT, ENTSO-E) and empirical econometrics
- Experience with computational tools for modeling constrained networks (e.g., Python, R, or Stata)
- Ability to work with large datasets and perform statistical analysis
- Proficiency in English for academic writing and communication
- Open to applicants with a Master's degree or equivalent in Economics, Energy Systems, or a related field
- No specific nationality or residency restrictions mentioned
Funding & terms
How to apply
Deadline: 2026-11-05 (Europe/Madrid)
Applicants must submit their application through the official UPV/EHU portal for PhD positions. The application process requires uploading a CV, a research proposal, academic transcripts, and letters of recommendation. Detailed instructions and the application form are available on the university’s research management website. Ensure all required documents are submitted by the deadline to be considered.
- CV
- Research proposal (detailed outline of the intended PhD project)
- Academic transcripts (Bachelor’s and Master’s degrees)
- Letters of recommendation (typically 2-3)
- Proof of English proficiency (if applicable)
Contact
UPV/EHU Research Office· PhD Admissions
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