UC Berkeley

Over the past decades, two things have become increasingly apparent: first, climate change and associated environmental impacts are pressing issues, and second, despite this growing threat, existing policies still fall far short. The goal of my research, and what I hope for the field more broadly, is to achieve effective, efficient, and equitable policy. My dissertation research covers a wide range of topics, focusing on three different areas of energy and environmental economics: methane emissions from oil and gas production; flooding on agricultural land; and energy utility regulatory rates of return. The common thread is using applied economic tools and answering policy-relevant questions with data and analysis. Often, the data that are available are far from the ideal dataset, or the policies that are on the table are far from the first best. Here, my coauthors and I adopt the "economist as plumber" mindset, using the tools that are available to address the challenges at hand (Duflo 2017).

In my first chapter, my coauthor Wenfeng Qiu and I study emissions of methane, a powerful greenhouse gas, from oil and gas wells in the US. These emissions contribute significantly to climate change—they are approximately as large as the emissions of all fuel burned in the western US electricity grid. Methane emissions are rarely priced and lightly regulated—in part because they are hard to measure—leading to a large climate externality. However, measurement technology is improving, with remote sensing and other techniques opening the door for policy innovation. We present a theoretical model of emissions abatement at the well level and a range of feasible policy options, then use data constructed from cross-sectional scientific studies to estimate abatement costs. We simulate audit policies under realistic constraints, varying the information the regulator uses in choosing wells to audit. These policies become more effective when they can target on well covariates, detect leaks remotely, and charge higher fees for leaks. We estimate that a policy that audits 1% of wells with uniform probability achieves less than 1% of the gains of the infeasible first best. Using the same number of audits targeted on remotely sensed emissions data achieves gains of 30–60% of the first best. These results demonstrate that, because leaks are rare events, targeting is essential for achieving welfare gains and emissions reductions. Auditing a small fraction of wells can have a large impact when properly targeted. Our approach highlights the value of information in designing policy, centering the regulatory innovation that is possible when additional information becomes available.

My second chapter is coauthored with Oliver Browne, Alyssa Neidhart, and Dave Sunding. We study high-frequency flood risk on agricultural land. Floods destroy crops and lower the value of agricultural land. Economic theory implies that the hedonic discount on the value of a parcel of flood-prone land should scale with the expected probability flooding. Most empirical studies of the impact of flood risk on property values in the United States focus on the relatively small risk posed by the 100-year or 500-year floodplains, as reported in maps produced by the FEMA. These studies consequently find a relatively small corresponding discount in property values. However, a significant amount of agricultural bottom-land lies in floodplains that flood more frequently. We estimate the hedonic discounts on with agricultural land that floods at these higher frequencies along the Missouri River. As flood risk increases, the value of flood-prone land decreases, with a hedonic discount ranging from close to zero in the 500-year floodplain to approximately 17% in the 10-year floodplain. To illustrate the importance of characterizing these higher frequency flood risks, we consider a climate change scenario, where properties that already face some flood risk are expected to flood more frequently. My third chapter, coauthored with Stephen Jarvis, examines the regulated rate of return on equity utility companies are allowed to collect from their customers. Utilities recover their capital costs through regulator-approved rates of return on debt and equity. The US costs of risky and risk-free capital have fallen dramatically in the past 40 years, but these utility rates of return have not. We estimate the gap between what utilities are paid now, and what they would have been paid if their rate of return had followed capital markets, using a comprehensive database of utility rate cases dating back to the 1980s. We estimate that the current average return on equity is 0.5–4 percentage points higher than historical relationships would suggest, and consumers pay an average of $2–8 billion per year more than they would otherwise. We then revisit the effect posited by Averch and Johnson (1962), estimating the consequences of this incentive to own more capital: a 1 percentage point increase in the return on equity increases new capital investment by about 5% in our preferred estimate.