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 paper documents a shift in energy consumption toward residential usage during the COVID-19 pandemic in the United States. Focusing on electricity, I find a 7.9% increase in residential consumption, and a 6.9% and 8.0% reduction in commercial and industrial usage, respectively, from a monthly panel of electric utilities. Natural gas consumption also shifted toward residential use, so that aggregate electricity and gas expenditure only fell by 1% on net during a period in which GDP fell by 5%. Hourly smart meter data from Texas reveal how daily routines changed during the pandemic, with residential electricity usage during weekdays closely resembling those of weekends. In total, residential energy expenditures were an estimated $13B higher during Q2-Q4 2020, with the largest increases occurring in areas with a greater propensity to work from home. I find that transportation fuel consumption declined about 16%, so that total energy consumption in the U.S. economy fell by 8%.

This paper applies principles of adverse selection to overcome obstacles that prevent the implementation of Pigouvian policies to internalize externalities. Focusing on negative externalities from production (such as pollution), we evaluate settings in which aggregate emissions are known, but individual contributions are unobserved by the government. We propose giving firms the option to pay a tax on their voluntarily and verifiably disclosed emissions, or pay an output tax based on the average of rate of emissions among the undisclosed firms. The certification of relatively clean firms raises the output-based tax, setting off a process of unraveling in favor of disclosure. We derive sufficient statistics formulas to calculate the welfare of such a program relative to mandatory output or emissions taxes. We find that our mechanism would deliver significant gains over output-based taxation in two empirical applications: methane emissions from oil and gas fields, and carbon emissions from imported cement. ∗We are grateful to Thom Covert, Meredith Fowlie, Michael Greenstone, Suzi Kerr, Gib Metcalf, Mark Omara, James Sallee, Joseph Shapiro, Andrei Shleifer, Allison Stashko, Bob Topel and seminar participants at Yale, Harvard, the Utah Winter Business Economics Conference, UC Santa Barbara, UC Berkeley, and the University of Chicago for helpful comments. Iván Higuera-Mendieta provided excellent research assistance. Cicala gratefully acknowledges funding from the 1896 Energy and Climate Fund at the University of Chicago, and along with Olsen thanks the University of Zurich for hospitality. All errors remain our own. e-mail: scicala@gmail.com, david.hemous@gmail.com, graugaardolsen@gmail.com

This paper evaluates changes in electricity generation costs caused by the introduction of market mechanisms to determine production in the United States. I use the staggered transition to markets from 1999 to 2012 to estimate the causal impact of liberalization using a differences-in-difference design on a comprehensive hourly panel of electricity demand, generators’ costs, capacities, and output. I find that markets reduce production costs by 5 percent by reallocating production: gains from trade across service areas increase by 55 percent based on a 25 percent increase in traded electricity, and costs from using uneconomical units fall 16 percent. (JEL L51, L94, L98, Q41, Q48)

This paper uses monthly zip code-level data on electricity disconnections in Illinois to document the socioeconomic correlates of extreme economic distress among 5 million customers. In 2018-2019, cus-tomers in Black and Hispanic zip codes were about 4 times more likely to be disconnected for non-payment, 2-3 times more likely to be on deferred payment plans, and 70% more likely to participate in utility-based low-income assistance programs, controlling for zip code distributions of income and other demographic characteristics. During the COVID-19 pandemic, there has been a ninefold expansion in low-income assistance to pay utility bills, but disconnections were double and deferred payment plans triple their historical averages in October 2020. Disconnection notices were served to 2.5% of commercial and industrial accounts, and 3.4% of residential accounts each month in late 2020. About 20% of all accounts were charged late fees. The odds for each of these measures were multiples higher in minority zip codes. (c) 2021 Elsevier B.V. All rights reserved.

The COVID-19 pandemic resulted in stay-at-home policies and other social distancing behaviors in the United States in spring of 2020. This paper examines the impact that these actions had on emissions and expected health effects through reduced personal vehicle travel and electricity consumption. Using daily cell phone mobility data for each U.S. county, we find that vehicle travel dropped about 40% by mid-April across the nation. States that imposed stay-at-home policies before March 28 decreased travel slightly more than other states, but travel in all states decreased significantly. Using data on hourly electricity consumption by electricity region (e.g., balancing authority), we find that electricity consumption fell about 6% on average by mid-April with substantial heterogeneity. Given these decreases in travel and electricity use, we estimate the county-level expected improvements in air quality, and, therefore, expected declines in mortality. Overall, we estimate that, for a month of social distancing, the expected premature deaths due to air pollution from personal vehicle travel and electricity consumption declined by approximately 360 deaths, or about 25% of the baseline 1500 deaths. In addition, we estimate that CO2 emissions from these sources fell by 46 million metric tons (a reduction of approximately 19%) over the same time frame.

The average effect of deregulatory policies on fuel prices at coal-fired power plants is strongly influenced by plants that were initially paying the highest prices for fuel. Primary sources document that these plants were locked into long-term, high-cost fuel contracts, and only secured market rates post-deregulation. While these plants' fuel costs were unusual, their response to deregulation was not: both coal- and gas-fired plants reduce fuel prices one-for-one with the amount they were initially paying above their neighbors' costs. Our understanding of deregulation is not improved by excluding those who stand to benefit most. (JEL L51, L71, L94, L98, Q35, Q41, Q48)

This paper documents an increase in residential electricity consumption while industrial and commercial consumption has fallen during the COVID-19 pandemic in the United States. Hourly smart meter data from Texas reveals how daily routines changed during the pandemic, with usage during weekdays closely resembling those of weekends. The 16% residential increase during work hours offsets the declines from commercial and industrial customers. Using monthly data from electric utilities nationwide, I find a 10% increase in residential consumption, and a 12% and 14% reduction in commercial and industrial usage, respectively, during the second quarter of 2020. This contrasts with the financial crisis of 2008, which also witnessed a rapid decline in industrial electricity consumption, but left residential usage unaffected. The increase in residential consumption is found to be positively associated with the share of the labor force that may work from home. From April through July of 2020, total excess expenditure on residential electricity was nearly $6B.

This paper presents preliminary estimates of how electricity consumption has changed in the European Union since the spread of COVID-19, as a proxy for short-term changes in economic activity. I collect hourly data by country from European Network of Transmission System Operators for Electricity (ENTSO-E) from 2016-present, and match it with automated weather stations to adjust for heating and cooling demand. As of the week ending 4 April, 2020, power consumption is down roughly 10%, with large differences across countries reflecting the timing and stringency of lockdown policies. ∗I am grateful to Francesco Decarolis, Tommaso Monacelli, and Justin Wolfers for helpful conversations. Iván Higuera-Mendieta provided excellent research assistance under unusual circumstances. Ari Anisfeld, Chinmay Lohani, and H.I. Park also pitched in on short notice. This research is funded by the Political Economics Initiative at the Becker Friedman Institute at the University of Chicago. All errors remain my own. e-mail: scicala@gmail.com

A health insurer's Medical Loss Ratio (MLR) is the share of premiums spent on medical claims, or the inverse markup over average claims cost. The Affordable Care Act introduced minimum MLR provisions for all health insurance sold in fully insured commercial markets, thereby capping insurer profit margins, but not levels. While intended to reduce premiums, we show this rule creates incentives to increase costs. Using variation created by the rule's introduction as a natural experiment, we find medical claims rose nearly one-for-one with distance below the regulatory threshold: 7 percent in the individual market and 2 percent in the group market. Premiums were unaffected. (JEL G22, H51, I13, I18)

We propose a model of social interactions based on comparative advantage. When comparative advantage is the guiding principle of social interactions, the effect of moving a student into an environment with higher-achieving peers depends on where in the ability distribution she falls and the shadow prices that clear the social market. We show that the model’s key prediction -- an individual’s ordinal rank predicts her behavior and test scores, ceteris paribus -- is borne out in one randomized controlled trial in Kenya as well as two large observational data sets from the U.S. To test whether comparative advantage can explain the effect of rank on outcomes, we conduct an experiment with nearly 600 public school students in Houston. The experimental results suggest that social interactions are, at least in part, governed by comparative advantage.

A health insurer's Medical Loss Ratio (MLR) is the share of premiums spent on medical claims. The Affordable Care Act introduced minimum MLR provisions for all health insurance sold in fully-insured commercial markets, thereby capping insurer profit margins, but not levels. While intended to reduce premiums, we show this rule creates incentives analogous to cost of service regulation. Using variation created by the rule's introduction as a natural experiment, we find claims costs rose nearly one-for-one with distance below the regulatory threshold: 7% in the individual market, and 2% in the group market. Premiums were unaffected.

We develop a Roy model of social interactions in which individuals sort into peer groups based on comparative advantage. Two key results emerge: First, when comparative advantage is the guiding principle of peer group organization, the effect of moving a student into an environment with higher-achieving peers depends on where in the ability distribution she falls and the effective wages that clear the social market. In this sense our model may rationalize the widely varying estimates of peer effects found in the literature without casting group behavior as an externality in agents' objective functions. Second, since a student's comparative advantage is typically unobserved, the theory implies that important determinants of individual choice operate through the error term and may, even under random assignment, be correlated with the regressor of interest. As a result, linear in means estimates of peer effects are not identified. We show that the model's testable prediction in the presence of this confounding issue-an individual's ordinal rank predicts her behavior, ceteris paribus-is borne out in two data sets.

Empirical estimates of peer effects vary widely in the literature. To better understand the conflicting evidence, we develop a price theory of social interactions in which peer group membership is dictated by comparative advantage. Two key results emerge from the model. First, when comparative advantage is the guiding principle of peer group organization, the effect of transplanting a student into an environment with higher-achieving peers depends on where in the ability distribution she falls and the effective wages that clear the social market. Second, since social wages and a student’s comparative advantage are typically unobserved, the theory implies that important determinants of individual choice operate through the error term and may, even under random assignment, be correlated with the regressor of interest. As a result, under the assumptions of our model, linear in means estimates of peer effects are not identified. We show that the model’s testable prediction in the presence of this confounding issue–an individual’s ordinal rank predicts her behavior, ceteris paribus–is borne out in two data sets. ∗We are grateful to Edward Glaeser, Bryan Graham, Richard Holden, Lawrence Katz, Steven Levitt, Franziska Michor, Chris Shannon, Andrei Shleifer, Glen Weyl, and seminar participants in the Harvard Labor Lunch for helpful comments and suggestions. We thank Lisa Sanbonmatsu for her assistance obtaining data from the Moving to Opportunity Experiment, which were used in an earlier draft of this paper. Vilsa E. Curto, Ryan Fagan, and Wonhee Park provided excellent research assistance. Financial support from the Weatherhead Center for International Affairs [Cicala], the Education Innovation Lab at Harvard University [Fryer], and the German National Academic Foundation [Spenkuch] is gratefully acknowledged. Correspondence can be addressed to the authors at Department of Economics, Harvard University, 1805 Cambridge Street, Cambridge MA 02138 [Cicala or Fryer]; Department of Economics, University of Chicago, 1126 E 59th Street, Chicago IL 60637 [Spenkuch]; or by e-mail: scicala@fas.harvard.edu [Cicala], rfryer@fas.harvard.edu [Fryer], or jspenkuch@uchicago.edu [Spenkuch]. The usual caveat applies.