CS28: Energy Markets

Modern power systems have evolved beyond mere physical energy delivery grids, transforming into massive data networks where millions of Distributed Energy Resources (DERs), smart meters, and sensors exchange information in real time. Driven by this transition, the importance of energy data is surging, leading to the emergence of Energy Data Markets designed to trade and utilize this critical asset. Crucially, energy data transactions are rarely one-off purchases. Rather, they occur in a continuous and iterative manner, typically through API-based data streaming or subscription service style. Within this continuous trading environment, data sellers are exposed to moral hazard incentives, whereby they may gradually reduce the effort required to maintain data quality or sustain reliable data collection. However, traditional static mechanism design approachs exhibit significant limitations in addressing these temporal dynamics and controlling continuous hidden actions. To address this gap, this study proposes the application of Continuous-Time Dynamic Contracting represented by Sannikov (2008) to energy data and power data markets. Specifically, by analyzing mechanism design strategies grounded in Incentive Compatibility (IC) and Individual Rationality (IR) constraints, we demonstrate the potential impact and efficacy of the proposed research framework within the broader energy sector.

In the early 2000s, Brazil occupied a vulnerable position in international oil markets, marked by dependence on crude oil imports and limited export relevance. Over the following two decades, this position changed substantially due to the discovery and large-scale development of pre-salt reserves, rising domestic production, and shifts in global energy demand. By 2024, Brazil had consolidated itself as a net exporter of crude oil while remaining structurally dependent on imported refined products, generating a persistently positive aggregate trade balance anchored in upstream competitiveness.
The article develops a structural analysis of Brazil's external trade in crude oil and refined products between 2000 and 2024 using a systematic set of synthetic trade indicators grounded in international trade theory. It applies the Revealed Comparative Advantage Index (CTB), the Relative Market Position Index (POS), and the Regional Orientation Index (IOR), alongside an adapted Regional Import Intensity Index (IIRI). These measures are jointly combined with CR4 concentration indicators by product and trading partner, allowing a consistent assessment of specialization, competitiveness, geographic orientation, and relational concentration across products, flows, and time.
The results identify a persistent dual structure. Brazil exhibits stable comparative advantage and net export position in crude oil, while refined products show sustained comparative disadvantage and import dependence. Crude oil exports become increasingly oriented toward Asia, particularly China, whereas refined-product imports remain concentrated in suppliers from the Gulf of Mexico-especially the United States-and, more recently, Russia.
The evidence shows that Brazil's positive petroleum trade balance is structurally driven by crude oil exports rather than downstream self-sufficiency. This configuration strengthens external competitiveness but preserves vulnerability to refining margins, logistical disruptions, and geopolitical shocks, highlighting a persistent trade-off between upstream strength and downstream dependence.

Electricity market deregulation, notably in Texas, aims to boost efficiency through competition. This research analyzes the retail electricity segment in Texas to evaluate its competitiveness. We utilize a theoretical Stackelberg price competition model for differentiated markets with two dominant players and a competitive fringe. Our theoretical predictions posit that increased competition reduces both price dispersion and overall prices.
Our empirical investigation uses a large monthly panel dataset from 2022 to 2025, compiled from Texas' Power to Choose data, wholesale electricity rates from ERCOT, and ZIP-code-level demographics. We employ panel data regression analysis to test the model's predictions, specifically examining how competition and concentration affect price dispersion, and identifying the determinants of retail prices.
A descriptive analysis shows a decrease in market concentration alongside an increase in weighted retail electricity prices during the study period. This trend might be attributable to post-Uri regulatory changes that raised retailers' costs (both fixed and financial), as well as the potential exercise of market power.
Preliminary regression findings align with our theoretical model, suggesting that dominant firms charge higher prices. However, we found no significant evidence that competition negatively affects price dispersion. The analysis also uncovers several influential features of retail pricing plans. Prices tend to increase as retailers' reputations and refund commitments improve. Higher wholesale price volatility is associated with higher retail prices, likely due to increased hedging costs. Conversely, prices decrease when cancellation fees or renewable content are higher. This may be explained by the fact that smaller, newer firms tend to provide services with greater renewable content. Additionally, retailers tend to charge less in areas with younger populations and more in densely populated areas or areas with older populations. Our results can help to shed light on the price mechanism of retail electricity and inform future regulatory policy decisions.

Energy price elasticities are a key variable in designing policies that address sustainability, efficiency, and equity concerns. However, estimating consumer responses to price changes is challenging due to simultaneous demand shocks, regulatory constraints, and complex consumer behavior. This paper estimates the short- and long-term price elasticity of residential energy consumption using a natural experiment based on the implementation of a Social Electricity Tariff in Tucumán, Argentina. The policy, designed to support vulnerable households, subsidized the fixed charge of the electricity tariff but initially benefited only a small subset of highly vulnerable users. We employ a difference-in-differences approach, using low-income households initially excluded from the subsidy as the control group. Our findings indicate that price elasticity is inelastic, with a stronger effect among lower-consumption users. To our knowledge, this study provides the first quasi-experimental estimate of short- and long-term price elasticity for Latin America, offering valuable insights for energy policy design.

The New Gas Market initiative represents the Brazilian Federal Government's ambitious pursuit to foster an open, dynamic, and highly competitive natural gas market. However, we note that there are still barriers in this market, mainly with regard to promoting competition and encouraging sales in the free gas market in the country. This work constructs a risk analysis model for natural gas commercialization, assessing risk-return and performance metrics to gauge the risk appetite of intermediaries handling gas transactions. Using a mean reversion process for Brent prices, we predict natural gas purchase prices and evaluate the trader's tolerance for oil price fluctuations using metrics like Value at Risk, Conditional Value at Risk and Omega measure. The objective of this model is to enhance the natural gas market in Brazil by assisting the trader in its risk analysis. Our main findings indicate an opportunity for traders to offer fixed natural gas prices to industrial clients, benefiting them. However, it also highlights the risk of exposure to oil price fluctuations, emphasizing the importance of conducting thorough risk analysis. For future research, we suggest exploring hedging and derivative models like swap analysis and collar options.