@article{JerrentrupLotzTiedemannetal., author = {Jerrentrup, Lars and Lotz, Bastian and Tiedemann, Silvana and Hirth, Lion}, title = {Technology-Neutral Auctions for Renewable Energy: EU Law vs. Member State Reality}, series = {Journal for European Environmental \& Planning Law}, volume = {16}, journal = {Journal for European Environmental \& Planning Law}, edition = {4}, issn = {1876-0104}, doi = {10.1163/18760104-01604005}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:b1570-opus4-30906}, pages = {386 -- 406}, abstract = {European Union competition law, intended to thwart subsidies paid out by national governments, plays an important role in shaping EU Member States' support schemes for renewable energy. The Environmental and Energy State Aid Guidelines 2014-2020, which formalize the European Commission's take on subsidies in the electricity sector, prescribe technology-neutral auctions as the standard mechanism to determine support levels. In this study, we have assessed the formal decisions of the Commission with respect to technology-neutrality between July 2014 and May 2018. It turns out that 16 out of 18 schemes are not technology-neutral and figure high degrees of technology-differentiation. We have also studied the exemption clauses invoked to justify technology-discrimination, finding that the most ambiguous clause is used most frequently, and that the application and level of scrutiny varies strongly from case to case. The State Aid Guidelines are meant to increase transparency and legal certainty. We find that with respect to technology-neutral auctions for renewable energy, the Guidelines fail to deliver on their purpose.}, language = {en} } @techreport{TiedemannSanchezCanalesSchuretal., type = {Working Paper}, author = {Tiedemann, Silvana and Sanchez Canales, Jorge and Schur, Felix and Sgarlato, Raffaele and Hirth, Lion and Ruhnau, Oliver and Peters, Jonas}, title = {Identifying Elasticities in Autocorrelated Time Series Using Causal Graphs}, publisher = {arXiv}, doi = {10.48550/arXiv.2409.15530}, pages = {37}, abstract = {The price elasticity of demand can be estimated from observational data using instrumental variables (IV). However, naive IV estimators may be inconsistent in settings with autocorrelated time series. We argue that causal time graphs can simplify IV identification and help select consistent estimators. To do so, we propose to first model the equilibrium condition by an unobserved confounder, deriving a directed acyclic graph (DAG) while maintaining the assumption of a simultaneous determination of prices and quantities. We then exploit recent advances in graphical inference to derive valid IV estimators, including estimators that achieve consistency by simultaneously estimating nuisance effects. We further argue that observing significant differences between the estimates of presumably valid estimators can help to reject false model assumptions, thereby improving our understanding of underlying economic dynamics. We apply this approach to the German electricity market, estimating the price elasticity of demand on simulated and real-world data. The findings underscore the importance of accounting for structural autocorrelation in IV-based analysis.}, language = {en} } @techreport{Tiedemann, type = {Working Paper}, author = {Tiedemann, Silvana}, title = {How to Estimate and Interpret the Response of Electricity Consumers to Real-Time Pricing}, publisher = {SSRN}, doi = {10.2139/ssrn.5140165}, pages = {40}, abstract = {The shift toward renewable energy sources in electricity markets increases the need for demand-side flexibility. One way to better coordinate demand and supply is through real-time pricing, but the extent to which consumers adjust their demand in response is an ongoing debate. Estimating this effect is challenging due to the endogenous nature of electricity prices, leading to potentially biased estimates. This paper compares three methodological approaches—adding exogenous control variables, instrumental variable (IV) regression, and using a control group—to assess their suitability for identifying the demand response of electricity consumers to real-time pricing. Using directed acyclic graphs (DAGs) and simulations, the article illustrates the conditions under which each approach is valid. It uses methodological insights to re-analyze data from a study on Spanish residential electricity consumers. The results confirm previous findings that consumers under real-time pricing do not respond to quasi-random, short-term price fluctuations. However, the panel regression suggests that they may adjust consumption based on expected price patterns, relying on heuristics rather than real-time monitoring of prices. This finding underscores the importance of selecting appropriate estimation methods and highlights the potential for systematic misinterpretation of demand response estimates. The study concludes with recommendations for which method to use, given the research question and the data at hand.}, language = {en} } @techreport{TiedemannSgarlatoHirth, type = {Working Paper}, author = {Tiedemann, Silvana and Sgarlato, Raffaele and Hirth, Lion}, title = {Price elasticity of electricity demand: Using instrumental variable regressions to address endogeneity and autocorrelation of high-frequency time series}, publisher = {arXiv}, doi = {10.48550/arXiv.2306.12863}, pages = {25}, abstract = {This paper examines empirical methods for estimating the response of aggregated electricity demand to high-frequency price signals, the short-term elasticity of electricity demand. We investigate how the endogeneity of prices and the autocorrelation of the time series, which are particularly pronounced at hourly granularity, affect and distort common estimators. After developing a controlled test environment with synthetic data that replicate key statistical properties of electricity demand, we show that not only the ordinary least square (OLS) estimator is inconsistent (due to simultaneity), but so is a regular instrumental variable (IV) regression (due to autocorrelation). Using wind as an instrument, as it is commonly done, may result in an estimate of the demand elasticity that is inflated by an order of magnitude. We visualize the reason for the Thams bias using causal graphs and show that its magnitude depends on the autocorrelation of both the instrument, and the dependent variable. We further incorporate and adapt two extensions of the IV estimation, conditional IV and nuisance IV, which have recently been proposed by Thams et al. (2022). We show that these extensions can identify the true short-term elasticity in a synthetic setting and are thus particularly promising for future empirical research in this field.}, language = {en} } @article{TiedemannMuellerHansen, author = {Tiedemann, Silvana and M{\"u}ller-Hansen, Finn}, title = {Auctions to phase out coal power: Lessons learned from Germany}, series = {Energy Policy}, volume = {174}, journal = {Energy Policy}, doi = {10.1016/j.enpol.2022.113387}, abstract = {This study assesses the extent to which auctions for compensation payments are a suitable policy instrument for ending coal-fired power generation at minimum cost and thus achieving national climate targets. Germany is the first country to apply such a market-based mechanism. Evaluating the effectiveness and efficiency of the auction, we find that the first five of seven auction rounds will retire 10 GW of coal-fired capacity at a cost of 68 ± 5 EUR/kW, corresponding to an additional carbon price of 2.4 ± 0.2 EUR/tCO2. The possibility of administratively shutting down power plants from 2024 and a decreasing ceiling price have ensured that average compensation payments are well below the ceiling price, and low compared to other policies, even though there was no competition in two of five auction rounds. As the government cancels the freed emission allowances, the policy will result in lower emissions, even though the carbon intensity of the German coal power fleet increased slightly by 2\%. Thus, the German auctions can serve as a model for national phase-out strategies in countries with similar institutional frameworks and provide a reference case for integrating conflicting policy objectives into auctions.}, language = {en} } @techreport{TiedemannStieweKratzkeetal., type = {Working Paper}, author = {Tiedemann, Silvana and Stiewe, Clemens and Kratzke, Corinna and Hirth, Lion and Jentsch, Mareike and Damm, Nicolai and Gerhardt, Norman and Pape, Carsten}, title = {Gebotszonenteilung: Auswirkungen auf den Marktwert der Erneuerbaren Energien im Jahr 2030}, publisher = {Kopernikus-Projekt Ariadne}, address = {Potsdam}, doi = {10.48485/pik.2024.002}, pages = {49}, abstract = {Eine Teilung des deutschen Marktgebietes w{\"u}rde die Marktwerte erneuerbarer Energien beeinflussen. Wind und Photovoltaik (PV) im S{\"u}den Deutschlands w{\"u}rden an Wert gewinnen, w{\"a}hrend Erneuerbare im Norden Erl{\"o}se einb{\"u}ßen w{\"u}rden. Bei einer auch zuk{\"u}nftig st{\"a}rkeren Konzentration von erneuerbaren Energien im Norden bedeutet dies insgesamt einen h{\"o}heren F{\"o}rderbedarf f{\"u}r PV - Wind w{\"a}re trotz niedriger Marktwerte in den meisten Regionen wirtschaftlich. Wenn eine regionale Steuerung erreicht werden soll, m{\"u}sste die auszuzahlende F{\"o}rderung f{\"u}r neue PV-Anlagen anhand des zonen{\"u}bergreifenden Referenzmarktwertes berechnet werden. Durchschnittliche B{\"o}rsenstrompreise w{\"u}rden durch eine Gebotszonenteilung im S{\"u}den Deutschlands leicht angehoben und im Norden gesenkt, die Effekte auf Endkundenpreise und damit verbundene Anreize zur Standortwahl von Industrieunternehmen sind allerdings als gering einzusch{\"a}tzen.}, language = {de} } @techreport{BurkhardtBillerbeckBoettgeretal., type = {Working Paper}, author = {Burkhardt, Alexander and Billerbeck, Anna and B{\"o}ttger, Diana and Brand, Heike and Egerer, Jonas and Gerhardt, Norman and Gillich, Annika and Held, Anne and Kahles, Markus and Kamm, Johanna and Hoff, Felix and Kochems, Johannes and Nienhaus, Kristina and Pfefferer, Ulrike and Radke, Silvian and Schill, Wolf-Peter and Stecher, Michael and Stiewe, Clemens and Tekin, Erdal and Tiedemann, Silvana}, title = {Kernelemente des Strommarktdesigns - Anforderungen, Ziele, Bewertungskriterien und Handlungsoptionen}, publisher = {Kopernikus-Projekt Ariadne}, address = {Potsdam}, doi = {10.48485/pik.2024.016}, pages = {39}, language = {de} } @techreport{HirthTiedemannSchill, type = {Working Paper}, author = {Hirth, Lion and Tiedemann, Silvana and Schill, Wolf-Peter}, title = {Was sind eigentlich Netzentgelte?}, publisher = {Kopernikus-Projekt Ariadne}, address = {Potsdam}, doi = {10.48485/pik.2024.020}, pages = {8}, language = {de} } @phdthesis{Tiedemann, author = {Tiedemann, Silvana}, title = {Essays in empirical energy economics: Real-time electricity pricing, energy saving rewards, and auctions in the energy transition}, school = {Hertie School}, pages = {264}, abstract = {The transition to a sustainable energy system requires a balance between climate protection, economic efficiency, and energy security. This dissertation contributes to understanding how to achieve these policy goals by evaluating the effect of real-time pricing on demand-side flexibility, financial incentives for energy savings, and auction-based steering of the national capacity mix. The two articles in the first part examine the challenges of estimating the response of electricity demand to real-time pricing. Despite theoretical expectations that dynamic pricing allows for flexible electricity consumption, empirical analyses show that consumers respond little to short-term fluctuations. However, they may systematically adjust consumption, providing a form of demand flexibility that is not captured by some econometric models. Moreover, time dynamics can bias results if not properly addressed. This work therefore advances our understanding of how to isolate different types of responses and how to interpret empirical findings. The article in the second part examines financial incentives for energy savings, focusing on gas saving rewards implemented during the European energy crisis of 2022/23. Analyzing micro-level consumption data, this research employs a matched control group design and the presently developed Double/Debiased Machine Learning estimator to show that direct financial incentives significantly reduce gas consumption. The two articles in the third part evaluate auctions to manage the national capacity mix. An evaluation of Germany's coal phase-out auctions shows that the mechanism was designed to balance competing policy objectives, resulting in relatively low compensation costs but increasing the carbon intensity of the remaining coal fleet. The study of renewable energy auctions estimates bidders' true costs and mark-ups, revealing significant heterogeneity in bidding strategies based on firm size and market experience. Overall, this dissertation provides empirical evidence for designing effective policies to advance the energy transition, drawing on econometric and causal methods. The findings underscore the need for tailored incentive structures and market mechanisms that are consistent with policy objectives, consumer behavior, and market dynamics.}, language = {en} }