Despite state and federal efforts to restructure wholesale power markets, regulated utilities continue to own generation, transmission, and distribution affiliates. This Article describes challenges vertical integration creates in different electricity markets and analyzes these problems using literatures in both economics and law. It argues that policymakers should quarantine rate regulated utilities to reduce utility incentives to self-deal and otherwise direct investment away from socially beneficial grid infrastructure. JEL Classification: K21, Antitrust Law; K23, Regulated Industries and Administrative Law; L43, Legal Monopolies and Regulation or Deregulation; L51, Economics of Regulation; L94, Electric Utilities
This paper examines a retrieval-augmented generation (RAG) customisation of artificial intelligence platform ChatGPT, using papers written by economist Professor Stephen Littlechild from the 1960s to the present, to create “SCL AI Agent” (SCL). SCL seeks to replicate and apply the thinking of Professor Littlechild. Establishing the corpus of Professor Littlechild’s papers, uploading it to ChatGPT and then instructing ChatGPT on how to understand that information and apply it, revealed the need for experimentation and learning-by-doing. Careful configuration sought to reduce hallucination and ensure well-informed responses delivered in Professor Littlechild’s style. Assessment of SCL by regulatory professionals who have had long interaction with Professor Littlechild rated SCL highly, particularly in respect of “insight,”“completeness” and “accuracy.” These assessors were less convinced of SCL’s ability to replicate Professor Littlechild’s written style. However, if users provided SCL with context to their questions and information on the audience for its answers, SCL did deliver responses tailored to those audiences. SCL itself and uncustomised ChatGPT were asked to assess SCL’s answers to the assessors’ questions. They both agreed on SCL’s superiority relative to uncustomised ChatGPT. SCL demonstrated a sophisticated, abstract understanding of Professor Littlechild’s scholarship, although its ability to replicate his imagination is less clear and merits further research. Creating AI agents of other economists and setting them to critique each other’s work could facilitate the more rapid dissemination of insight and understanding. JEL Classifications: A11, Role of Economics; Role of Economists; Market for Economists; C45, Neural Networks and Related Topics; D83, Search; Learning; Information and Knowledge; Communication; Belief; Unawareness; I23, Higher Education; Research Institutions; O33, Technological Change: Choices and Consequences; Diffusion Processes
This study examines the vulnerability of India’s energy-intensive and trade-exposed (EITE) industries to the European Union’s Carbon Border Adjustment Mechanism (CBAM) and evaluates whether a domestic emissions trading system (ETS) can mitigate these risks. Using data from the Annual Survey of Industries for 2015 to 2022, we estimate sector-level marginal abatement costs (MACs) using a stochastic frontier translog hyperbolic distance function. Results indicate a decline in technical efficiency over time and substantial heterogeneity in abatement costs across industries, with shadow prices ranging from USD 54.8/tCO 2 in cement to USD 453.9/tCO 2 in coke ovens (average: USD 238.3/tCO 2 ). MACs are negatively associated with carbon intensity, although formal tests provide limited evidence of a statistically significant non-linear relationship. Projected MACs remain relatively stable through 2030 under alternative decarbonization pathways. To assess trade-related risks, we construct a composite CBAM vulnerability index using carbon intensity, trade exposure, and economic dependence. Aluminium emerges as the most vulnerable sector, followed by iron and steel, while cement and chemicals exhibit comparatively limited exposure. ETS simulations indicate that low-cost sectors become permit suppliers as carbon prices increase. The findings suggest that a well-designed domestic carbon market, complemented by targeted support for vulnerable industries, can lower the overall cost of decarbonization, strengthen competitiveness, and enhance resilience to emerging carbon-related trade measures. JEL Classification: Q52, Pollution Control Adoption and Costs; Distributional Effects; Employment Effects; Q54, Climate; Natural Disasters and Their Management; Global Warming; Q58, Environmental Economics: Government Policy
This study investigates the intricate relationships between natural gas prices and electricity price volatility in India. For this purpose, we use Indian daily market data from April 2012 to May 2024 and examine asymmetric interconnection between energy market indicators. By looking at both spot and futures prices of natural gas, we uncover detailed insights into how these indicators are inter-related over diverse time periods. Our findings indicate that increases and decreases in electricity market return volatility substantially and differently affect natural gas spot and future prices, highlighting the high asymmetric sensitivity of natural gas prices to electricity market volatility. The effect on natural gas trading volumes, however, is more complex. Increases in return volatility reduce the traded volumes, indicating increased risk aversion among market participants. JEL Classification: Q41, Q42, Q43, C19
Crack spreads are a central measure of refinery profitability, yet they are often treated as exogenous differences between crude-oil and refined-product prices. We develop a structural dynamic model in which crack spreads arise endogenously from refined-product demand, crude-supply conditions, convex utilization costs, refinery complexity, hard capacity constraints, and costly production adjustment. The model shows that crack-spread dynamics depend on the source of shocks and the degree of capacity pressure. Demand-driven episodes generate strong positive comovement between refined-product prices and crack spreads, while supply-driven episodes can produce weaker or offsetting relationships. Adjustment frictions further create negative short-run comovement between changes in utilization and changes in spreads. Numerical comparative statics from an illustrative implementation show how the model’s mechanisms operate under alternative volatility, adjustment-cost, and capacitytightness scenarios. JEL Classification: D21, Firm Behavior: Theory; D22, Firm Behavior: Empirical Analysis
The integration of electricity markets is widely promoted for enhancing competition and energy security. However, its impact on emissions and renewable energy deployment remains unclear. This paper exploits the expansion of the Spanish-French electricity interconnector to estimate the effect of integration on the quantity and location of CO 2 emissions avoided by Spanish wind production and on electricity prices of both countries. I find that integration has increased the amount of emissions avoided in France but decreased that in Spain for each additional megawatt-hour of Spanish wind. Since the gain in France is smaller than the loss in Spain, the net marginal CO 2 abatement effect of Spanish wind has declined. On prices, the previously non-significant impact on French prices before the expansion becomes significant afterwards, highlighting cross-border merit order effect. I then calculate the cost of reducing 1 ton of CO 2 through the Spanish wind subsidy program. Before the expansion, Spanish consumers gained 29.6€/tCO 2 avoided. After the expansion, the merit order effect no longer offsets the subsidy cost, resulting in a net cost of 6.3€/tCO 2 . Meanwhile, French consumers benefit for free from the abatement of 2.5 megatonnes of CO 2 annually, financed at a cost of 150€/tCO 2 by the Spanish consumer post-expansion. Finally, I assess the marginal welfare effect of wind power, accounting for both emissions abatement and the price-induced reduction in producer surplus. The subsidy policy is welfare-improving if the social cost of carbon exceeds 67€/tCO 2 before the expansion and 72€/tCO 2 afterwards. JEL Classification : D61, Allocative Efficiency; Cost-Benefit Analysis; Q40, Energy: General; Q42, Alternative Energy Sources; Q52, Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
Green electricity tariffs marketed as "100% renewable" often rely on Energy Attribute Certificates (EACs), which allow a temporal mismatch between consumption and generation. This mismatch has raised concerns about the actual environmental impact of green electricity tariffs and the potential to mislead consumers. This paper examines German households' awareness and preferences regarding temporal matching. Based on a stated-choice experiment with randomized information treatments and over 1,000 participants, we find: (1) 85% of consumers are unaware of the mismatch; (2) informing them about the mismatch reduces willingness to pay (WTP) for green electricity from 46% to 39% in our full sample, with stronger and more significant effects in relevant sub-samples; and (3) an explicit guarantee of temporal matching does not significantly increase WTP. We interpret these findings as an information failure in current green electricity markets, where a non-negligible share of consumers likely base their purchase decisions on incorrect or incomplete information. Various measures could help mitigate it, including clearer definitions and greater transparency mandates, alongside voluntary industry standards and third-party verification.JEL Classification: D18, Consumer Protection; Q48, Energy: Government Policy
While energy justice articles abound, few consider the underlying institutional and regulatory foundations of energy justice challenges. In this article, I present and analyze these foundations through a discussion of the core and underlying tenets of energy justice, the historical developments in energy markets that have led to the present focus on justice, and energy justice metrics that decision-makers employ. I then present two case studies—energy insecurity and legacy fossil fuel community transitions—to illustrate the complex institutional foundations, and several potential solutions, of energy justice challenges. JEL Classification : D02, Institutions: Design, Formation, Operations, and Impact; A12, Relation of Economics to Other Disciplines
To reduce fuel poverty and work towards a fair energy transition, it is important to know the 'essential goods basket' of each household. This is then used to determine the income needed to live decently, taking prices into account. One component of this essential basket is a decent level of energy for housing. The main objective of this study is to estimate, using French public data, the minimum quantity of energy that would enable each household to meet its basic needs in its home, depending on its characteristics, its home and its location. Estimating minimum energy levels obviously reveals significant differences depending on the thermal quality of the dwelling (measured by an EPC rating). The type of dwelling and its surface area also have an impact. Household composition, on the other hand, does not appear to be statistically significant.
How should the grid evolve to accommodate growing demand and the increasingly competitive economics of renewable energy? Who should be responsible for making these decisions? This paper draws on lessons from electricity sector restructuring to examine how institutional frameworks influence investment decisions, contract negotiations, and power production. When regulated utilities are allowed to earn returns on capital investments that exceed their costs, they often overspend compared to scenarios where they bear the financial risk themselves. Additionally, they exert less effort in securing competitive contracts when they do not directly benefit from the savings. These inefficiencies are particularly pronounced when regulators face challenges in determining optimal actions. Evidence from the adoption of wholesale electricity markets highlights that traditional regulatory frameworks are poorly suited to capture the inter-regional efficiencies of renewable energy generation. Strategies to address these issues include implementing yardstick competition for local distribution utilities and expanding the use of competitive bidding for infrastructure projects. JEL Classification : L51, Economics of Regulation, L94, Electric Utilities
This study investigates and compares the profitability and welfare effects of investing in zero-carbon generation technologies (i.e., solar PV, onshore and offshore wind and nuclear) within the context of future low-carbon electricity systems. Using a partial equilibrium model calibrated to the electricity markets in Northwest Europe, a Monte Carlo cost simulation and a scenario-based sensitivity analysis, the analysis reveals that investments in renewables outperform investments in nuclear power when looking at the profitability and the aggregated financial welfare effects on other market participants. However, the profitability of nuclear power is less sensitive to changes in the electricity market and investments in additional capacity. Although investments in additional nuclear capacity result in a higher reduction of life-time greenhouse gas emissions and require less grid expansions than comparable investments in renewables, overall investments in nuclear result in more negative welfare effects than investments in renewables. JEL Classification: Q41, Energy: Demand and Supply; Prices; D58, Computable and Other Applied General Equilibrium Models
Given China's pressure to reduce energy use and the rise of Chinese residents' energy consumption in the last decades, it is of significance to investigate the energy consumption behaviors of Chinese households. This paper examines the impacts of energy efficiency labeling on Chinese households' use of domestic appliances, using the data from a national household survey (i.e., the Chinese General Social Survey) in 2015. Applying the propensity score matching (PSM) approach, we find a positive relationship between energy efficiency label and the use of domestic appliances, indicating the possible existence of rebound effect. This finding is significantly robust across a series of appliances and a battery of regression methods. The heterogeneity analysis yields that the effect of energy efficiency label on appliance use is heterogeneous in residential places, income level and head's gender of households. The findings shed light on how to better apply energy efficiency labeling programs.JEL Classification: Q48, Energy: Government Policy; C13, Estimation: General; C54, Quantitative Policy Modeling
This study addresses the scarcity of empirical estimates on the elasticity of production factor substitutions, a crucial parameter in general equilibrium models for policy analysis. Employing the non-linear least squares estimation method, we determine the elasticity of substitution between capital, labor, energy, and materials in the Constant Elasticity of Substitution model across Europe at both aggregate and sectoral levels. Through rigorous analysis, we identify the optimal nesting structure of the production function for our data, rejecting widely used CES functional forms such as Cobb-Douglas and Leontief. Our findings reveal changes in elasticity of substitution over time, with Eastern Europe exhibiting greater ease of substitution compared to Western Europe, particularly between capital and labor. While elasticities in tertiary sectors diverge over time, those in energy-intensive sectors converge, though they remain statistically different, underscoring the necessity of region-specific elasticity sets in CGE models.
In this study, we first estimate the impact of a mandatory time-of-use (TOU) pricing policy on the aggregate electricity load and find evidence for statistically significant load-shifting effects. Next, we develop a data-driven method to examine the impact of the TOU pricing policy on social benefits in the electricity industry, including reductions in fuel costs, greenhouse gas emissions, capital investment in generation capacity, transmission congestion, and ancillary services. Our estimates reveal that the TOU tariffs yielded social benefits equivalent to 4.5 percent of wholesale electricity generation costs. With tariff redesign, this percentage could increase to 7.6 percent. Our analysis suggests that, when formulating TOU tariffs, policymakers should prioritize their impact on capital investment, from which the majority of social benefits (98%) stem.
