Environmental Economics Seminars

EPA's National Center for Environmental Economics (NCEE) regularly hosts seminars on timely topics in environmental economics. Researchers from EPA, other federal agencies, and academia present current work, followed by a collegial discussion of this research. Topics are chosen based on relevance to current EPA issues and, more broadly, to issues of concern to the environmental economics research community. These topics include exploration of innovations in economic research methods as well as how research results can be used to improve environmental policy making.

Note: Hosting these seminars does not necessarily express or imply EPA approval or endorsement of the speaker’s views.

Note to media: Seminars are not open to the media. The purpose of all our seminars is to foster the free exchange of information. For media inquiries, please contact the Office of Public Affairs.

Upcoming and Recent Seminars

While subject to change, NCEE generally holds these seminars monthly at EPA headquarters. In-person attendance is typically restricted to EPA employees, but a virtual option is available for all invitees.

If you would like to be added to the distribution list for information about these seminars, please contact NCEE.

September 29, 2 - 3:30 pm (EST)

Sandy Sum, University of California-Davis

Who Gains from Drinking Water Regulation? Evidence from the 2006 Arsenic Rule and Infant Health

Limited evidence on the health eﬀects of water contaminants has stymied the development of more stringent drinking water regulation. We evaluate the eﬀects of the 2006 Final Arsenic Rule – a ﬁscally unpopular regulation which lowered the drinking water arsenic standard from 50 to 10 µ g/l – on infant health outcomes, a category not considered in prospective rulemaking. Leveraging exogenous variation in policy binding status induced by the geological distribution of arsenic, we estimate annual health beneﬁts of $85–303 million, shifting the beneﬁt–cost ratio from 0.74 to 1.23 at the low end. Beneﬁts largely accrue to Hispanic and Asian mothers despite widespread reductions in drinking water arsenic across populations, suggesting heightened sensitivity to arsenic exposure.

October 21, 1:30 - 3 pm (EST)

Elizabeth Sorenson-Montoya, Kansas State University

Privatization and Quality: Evidence from U.S. Drinking Water Systems

While the existing economic literature has extensively examined the effect of privatization on efficiency and profitability, its impact on quality remains underexplored. Understanding this relationship is particularly important in sectors where quality is essential for human health. This study investigates how privatizing U.S. drinking water systems affects quality. Given the competing incentives and regulatory pressures that influence a firm's quality decisions, the ultimate impact of privatization is theoretically ambiguous. Using hand-collected data on municipal systems sold to private companies and employing a propensity-weighted difference-in-differences approach, I find that privatization leads to 1.4 fewer Safe Drinking Water Act violations, a 20% decrease in an index of regulated contaminant concentrations, and a 30% decrease in an index for contaminants that pose an immediate threat to human health. These findings indicate that privatization leads to an overall improvement in drinking water quality and back-of-the-envelope estimates suggest economically meaningful benefits to public health, averaging at least $12.6 million per state in the sample.

November 10, 11 am - 12:30 pm (EST)

Ed Rubin, University of Oregon

Power Plants, Air Pollution, and Regulatory Rebound

We show that interactions between overlapping environmental regulations—particularly when one involves a threshold-based standard—can substantially attenuate the benefits predicted when policies are evaluated in isolation. This attenuation arises because conventional models and analyses typically assume local emissions are exogenous to upwind regulatory shocks. To study the impacts of this assumption, we develop a model in which threshold-based air-quality standards overlap with regulations targeting major point sources. We then empirically test the model’s predictions and document evidence consistent with regulatory rebound: when upwind power-plant emissions fall (e.g., due to point-source rules), local emissions in NAAQS-constrained areas rise. We find that regulatory rebound offsets 50–70 percent of expected PM₂.₅ improvements. To quantify rebound’s impact, we develop a high-resolution modeling framework that combines advanced particle-trajectory modeling (NOAA’s HYSPLIT) with machine learning to map upwind power-plant emissions to downwind air quality with state-of-the-art accuracy. We use these predictions to quantify how sustained reductions in upwind emissions of PM₂.₅ precursors affect downwind local PM₂.₅ concentrations. The results are consistent with local pollution rebounding in response to upwind emission reductions—particularly in NAAQS-constrained areas. Our findings underscore the importance of accounting for behavioral and regulatory interactions when designing and evaluating environmental policy—critical for efficiency and equity.

December 8, 10 - 11:30 am (EST)

Reid Taylor, Federal Reserve Bank of Dallas

Processing Power: The Effect of Data Centers on Wholesale Electricity Markets

Artificial-intelligence-driven data centers are reversing two decades of flat U.S. electricity demand and have generated questions about how this growth will impact electricity prices. We quantify this effect using an hourly, unit-level least-cost dispatch model covering wholesale electricity markets in the continental United States. We find that existing data centers have already increased wholesale prices by 3 to 5% on average nationwide, with substantially larger effects in regions hosting major data center corridors. Extending the model through 2028, we show that if proposed construction proceeds under high-utilization scenarios, wholesale prices could rise dramatically (50%), while more moderate build-out yields smaller (20%) but still meaningful effects. Impacts vary due to utilization and build-out assumptions. Finally, we use the model to address several policy discussions including optimal data center siting decisions and renewable build-out uncertainty.