Michael Greenstone
mgreenst@uchicago.edu
773-702-8250
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Christine Spencer: christines1@uchicago.edu
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Vicki Ekstrom High: vekstrom@uchicago.edu
April 2024
With the U.S. Environmental Protection Agency, we developed a machine learning model to predict sites where inspections would uncover severe violations of hazardous waste regulations. We estimate that using our model to target inspections will increase the “hit rate” by 46%. As is often the case, the model’s data are highly selected (representing about ~2% of sites), suggesting that classic selection bias concerns make our estimate’s relevance to the full population unknown. We therefore conducted a national field test of the model’s versus the EPA’s inspection targets; the model’s relative performance was even better, increasing the hit rate by 79%.
April 2024
Motor vehicle fuel-economy standards have long been a cornerstone of U.S. policy to reduce fuel consumption in the light-duty vehicle fleet. In 2010 and 2012, these standards were significantly expanded in an effort to achieve steep reductions in oil demand and greenhouse gas (“GHG”) emissions through 2025. In 2018, following a review of the standards, the Environmental Protection Agency and National Highway Traffic Safety Administration proposed instead to freeze the standards at 2020 levels, citing high program costs (and potential safety issues).
The current debate over the future of U.S. fuel economy standards provides an opportunity to consider whether the existing approach could be improved to achieve environmental and other goals at a lower cost. The current policy prescribes standards that focus on fuel economy alone, as opposed to lifetime consumption, and treats vehicle categories differentially, meaning that it imposes unnecessarily high costs and does not deliver guaranteed GHG savings.
On the basis of a commitment to cost-benefit analysis, which has defined U.S. regulatory policy for more than thirty years, we propose novel reforms with three main features: (1) the direct regulation of expected fuel consumption and GHG emissions without consideration of the type or size of the vehicle; (2) use of existing data to assign lifetime fuel consumption and GHG emissions to each model; and (3) creation of a robust cap-and-trade market for automakers to reduce compliance costs. We show that these reforms would reduce fuel consumption and GHG emissions in transportation with greater certainty and do so at a far lower cost per ton of GHG emissions avoided. We also show that the Environmental Protection Agency and the Department of Transportation could implement such an approach within their existing statutory authority.
Harvard Environmental Law Review, 2020, 44(1): 1-42.
Edward Balleisen and David Moss (eds.) Government and Markets: Toward a New Theory of Regulation, Cambridge; New York: Cambridge University Press, 2010, 52-91.
New regulation shouldn’t rely on old ideas. Since the 1960s, influential research on government failure helped to drive the movement for deregulation and privatization. Yet even as this branch of research was flourishing, very different ideas were sprouting in the social sciences with profound implications for our understanding of human behavior and the role of government. Some of these ideas, particularly from the field of behavioral economics, have begun to enter into discussions of regulatory purpose, design, and implementation. The process is far from complete, and many other exciting new lines of research – on everything from social cooperation to co-regulation – have hardly been incorporated at all. It is imperative that lawmakers and their constituents be able to draw on the very latest academic work in thinking anew about the role of government. This is the purpose of this book: to make the newest and most important research accessible to a broad audience.
David Moss and John Cisternino (eds.) New Perspectives on Regulation, Cambridge, MA: The Tobin Project, 2009, pp. 111-126.
Non-profit using the power of compliance markets to reduce + remove CO2 emissions, while supporting CDR tech innovation.
Accelerating organizations’ ability to achieve verifiable, scalable, and immediate carbon reduction + ultimate removal.