About

Fiona Burlig is an Assistant Professor at the Harris School of Public Policy and a Faculty Research Fellow at the National Bureau of Economic Research. She studies energy and environmental economics, with a focus on the developing world. Her recent research examines the impacts of rural electrification in India, uses machine learning methods to quantify the effectiveness of energy efficiency upgrades, and proposes tools for designing randomized controlled trials. Prior to joining Harris, Fiona was a Postdoctoral Scholar in the Department of Economics and Energy Policy Institute (EPIC) at the University of Chicago. She holds a PhD in agricultural and resource economics from the University of California, Berkeley, and a BA in economics, political science, and German from Williams College.

Research topics

• Computer Science
• Engineering
• Electrical engineering
• Artificial Intelligence
• Political Science
• Physics
• Sociology
• Economics
• Business
• Environmental economics
• Environmental science
• Mathematics
• Statistics
• Transport engineering
• Media studies
• Econometrics
• Law
• Optics

Selected publications

• If You Build It, They May Not Come: Willingness to Participate in Managed EV Charging

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• If You Build It, They May Not Come: Willingness to Participate in Managed EV Charging

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• If You Build It, They May Not Come: Willingness to Participate in Managed EV Charging

  National Bureau of Economic Research · 2026-04-01

  reportOpen access1st authorCorresponding

  Despite the importance of program participation for policy, treatment effects are often measured on self-selected samples.We study electric vehicle (EV) managed charging, intended to reduce electric grid strain by optimally allocating charging across EVs.Prior work finds large impacts of managed charging among households who volunteer for an RCT.In contrast, we test managed charging with an experiment including all EVs within a California utility.Enrollment is low even with high incentives, and we can reject even modest intent-to-treat effects on electricity consumption.Managed charging is less effective than previously thought, underscoring the value of population-wide experiments.

  PublisherDOI

• If You Build It, They May Not Come: Willingness to Participate in Managed EV Charging

  Federal Reserve Bank of Dallas, Working Papers · 2026-04-01

  article1st authorCorresponding
  PublisherDOI

• Reforming Energy Subsidies

  The MIT Press eBooks · 2026-03-10

  book-chapterOpen access1st authorCorresponding
  PublisherOA PDFDOI

• Data and Code for: The value of clean water: Experimental evidence from rural India

  ICPSR Data Holdings · 2026-02-19

  datasetOpen access1st authorCorresponding

  Over 2 billion people lack clean drinking water. Existing solutions face high costs (piped water) or low demand (point-of-use chlorine). Using a 60,000 household cluster-randomized experiment, we test an alternative approach: decentralized treatment and home-delivery of clean water to the rural poor. At low prices, take-up exceeds 90 percent, sustained throughout the experiment. High prices reduce take-up but are privately profitable. We experimentally recover revealed-preference measures of valuation. Willingness-to-pay is several times higher than prior indirect estimates; willingness-to-accept is larger and exceeds marginal cost. Self-reported health measures improve accordingly. On a cost-per-DALY basis, free water delivery regimes appear highly cost-effective.

  PublisherDOI

• Data and Code for: The value of clean water: Experimental evidence from rural India

  Open MIND · 2026-02-19

  datasetOpen access1st authorCorresponding

  Over 2 billion people lack clean drinking water. Existing solutions face high costs (piped water) or low demand (point-of-use chlorine). Using a 60,000 household cluster-randomized experiment, we test an alternative approach: decentralized treatment and home-delivery of clean water to the rural poor. At low prices, take-up exceeds 90 percent, sustained throughout the experiment. High prices reduce take-up but are privately profitable. We experimentally recover revealed-preference measures of valuation. Willingness-to-pay is several times higher than prior indirect estimates; willingness-to-accept is larger and exceeds marginal cost. Self-reported health measures improve accordingly. On a cost-per-DALY basis, free water delivery regimes appear highly cost-effective.

  OA PDFDOI

• The Value of Clean Water: Experimental Evidence from Rural India

  SSRN Electronic Journal · 2025-01-01

  articleOpen access1st authorCorresponding
  PublisherDOI

• The Value of Clean Water: Experimental Evidence from Rural India

  National Bureau of Economic Research · 2025-03-01 · 1 citations

  reportOpen access1st authorCorresponding

  Over 2 billion people lack clean drinking water. Existing solutions face high costs (piped water) or low demand (point-of-use chlorine). Using a 60,000 household cluster- randomized experiment, we test an alternative approach: decentralized treatment and home-delivery of clean water to the rural poor. At low prices, take-up exceeds 90 percent, sustained throughout the experiment. High prices reduce take-up but are privately profitable. We experimentally recover revealed-preference measures of valuation. Willingness-to-pay is several times higher than prior indirect estimates; willingness- to-accept is larger and exceeds marginal cost. Self-reported health measures improve accordingly. On a cost-per-DALY basis, free water delivery regimes appear highly cost- effective.

  PublisherDOI

• The Value of Clean Water: Experimental Evidence from Rural India

  SSRN Electronic Journal · 2025-01-01 · 1 citations

  preprintOpen access1st authorCorresponding
  PublisherDOI

Frequent coauthors

• Erin Kelley

  85 shared

• Gregory Lane

  82 shared

• Manzoor H. Dar

  75 shared

• Xavi Gine

  World Bank Group

  25 shared

• Amir Jina

  24 shared

• Catherine Wolfram

  Massachusetts Institute of Technology

  17 shared

• David Rapson

  14 shared

• Anant Sudarshan

  University of Warwick

  13 shared