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Research in Energy Economics Topics

Paper Session

Saturday, Jan. 4, 2020 12:30 PM - 2:15 PM (PDT)

Marriott Marquis, Coronado Room
Hosted By: International Association for Energy Economics
  • Chair: Alberto J. Lamadrid, Lehigh University

Dynamic Responses to Carbon Pricing in the Electricity Sector

Paige Weber
University of California-Santa Barbara and University of North Carolina-Chapel Hill


This paper investigates the impact of a regulation that prices carbon on an industry with dynamic production decisions. While carbon pricing is designed to reduce greenhouse gas (GHG) emissions, it also impacts the emissions of local air pollutants. I demonstrate that with dynamic production decisions it is theoretically possible for a carbon price in the electricity sector to increase pollution in some areas. However, the outcome depends on the empirical cost structure of the regulated firms. I develop a dynamic model of electricity production and generating unit efficiency investment decisions to analyze how firm decisions in California’s electricity sector are affected by the state’s carbon price. I use the model to simulate market outcomes across policy scenarios with and without carbon prices, as well as a location-specific Pigouvian tax on air pollutants. I show that under current carbon prices, the regulation leads to minimal production reallocation and small changes in the spatial distribution of local air pollutants compared to a no carbon price scenario. Higher carbon prices lead to production reallocation and co-benefits from changes in the spatial distribution of air pollutants; though, the co-benefits occur predominantly outside of state’s heavily polluted regions. On the other hand, the location-specific Pigouvian tax concentrates these benefits in heavily polluted regions. In addition, I demonstrate that under certain plausible conditions, private and social returns are largest when efficiency investments occur in the cleanest, most frequently utilized units.

Second Best Pricing for Incomplete Market Segments: Applications to Electricity Pricing

Nicolas Astier
Stanford University


Due to technological, political or practical considerations, simple rate structures prevail in many market segments. This reality contrasts with the fundamental theorems of welfare economics where prices are fully differentiated by time, location and contingency of delivery. This paper develops a tractable framework to design simple rate schedules under a large family of exogenous constraints. One can then easily assess the relative efficiency gains from using more complex price schedules and speculate about the absolute value of the benefits that may arise from R\&D or lobbying efforts to remove existing technological or political barriers. Conveniently, implementation relies on basic machine learning techniques and typically available information. Retail electricity pricing in both France and California are used as example applications.

Valuation of Drivers and Barriers to Smart Meter Adoption in the UK: A Survey Experiment

Daire McCoy
London School of Economics
Greer Gosnell
London School of Economics


To facilitate a sustainable energy transition, governments and innovators have encouraged the adoption of smart technologies in the home that allow for increased flexibility in centralized energy grids. The ambitious Smart Meter Implementation Programme in the United Kingdom has indisputably failed to achieve its objective of equipping all UK dwellings with smart meters by 2020, perhaps due to some or all of several identified barriers to adoption of allegedly welfare-enhancing energy technology in the home. By partnering with the UK's energy regulator, this research uses an incentive-compatible online experiment to elicit the willingness-to-accept of a representative panel of over 2,400 UK households for smart meter installation. Randomized information treatments allow for assessment of the impact on adoption and willingness-to-accept of several purported market failures in relation to smart meter adoption, namely information asymmetries regarding the personal and social benefits of smart meter adoption as well as information regarding accumulated positive `learning-by-using' externalities. We explore treatment effects for a range of potential subsidy values, and discuss implications for policymakers in encouraging residential smart meter adoption.

Market Power in Cost-Based Wholesale Electricity Markets: Evidence from Mexico

Shaun D. McRae


Market power is an important concern for designers of restructured wholesale electricity markets. In a cost-based market, the price and quantity offers of generation plants are set based on a regulatory formula. This market design is used for most electricity markets in Latin America, in part because it appears to eliminate the potential for dominant firms to exercise market power. In this paper I study the performance of the cost-based model in the newly restructured Mexican electricity market. I show that large generation firms still have the ability to exercise market power. This behavior would be difficult for the market operator to detect, given the informational asymmetry between firms and regulators. Using data for 2018, I show that both the generation offer prices and the market price are higher in hours when firms have greater ability to exercise market power.
Gregory B. Upton Jr.
Louisiana State University
Paul Joskow
Massachusetts Institute of Technology
Erin Baker
University of Massachusetts
Todd Gerarden
Cornell University
JEL Classifications
  • Q4 - Energy
  • L9 - Industry Studies: Transportation and Utilities