Hannah Druckenmiller
University Fellow
Hannah Druckenmiller is an environmental economist and assistant professor economics at the California Institute of Technology. Her research aims to provide empirically based estimates for the environmental benefits and economic costs associated with natural resource protection. For example, she has experience quantifying the flood mitigation value of natural lands, developing new approaches for accounting for ecosystem services in climate policy, and identifying cost-effective climate adaptation solutions.
Druckenmiller also has a strong interest in developing novel data and methods to enable progress on historically intractable problems in these areas of research. For example, she developed the spatial first differences research design in collaboration with Solomon Hsiang to identify causal effects in cross-sectional data. In ongoing work, she is applying machine learning to vast archives of historical aerial photography to better measure and understand long-run relationships between environmental change and human development.
Druckenmiller received her PhD in Agricultural and Resource Economics in 2021 from UC Berkeley, where she was a doctoral fellow at the Global Policy Lab and a NSF Graduate Research Fellow. She was a fellow at RFF between 2021 and 2023.
Education
- PhD in agricultural and resource economics, University of California, Berkeley, 2021
- MS in agricultural and resource economics, University of California, Berkeley, 2018
- BS in earth systems, Stanford University, 2014
Featured Content
- Highlights
- Publications
- Events
- Editorial
- News
Resources Radio — Mar 19, 2024
Mapping Waters of the United States Using New Tools, with Simon Greenhill and Hannah Druckenmiller
Simon Greenhill and Hannah Druckenmiller discuss a new machine learning model that can predict which rivers, streams, wetlands, and other waterways are regulated under the Clean Water Act according to different definitions of water bodies.
Common Resources — Jan 31, 2024
White House Rule on Clean Water Act in 2020 Dramatically Deregulated Waters of the United States
Machine learning can help reveal the complicated designation of which US waters are protected—or not—under various interpretations of the Clean Water Act.
Journal Article — Jan 25, 2024
Machine Learning Predicts Which Rivers, Streams, and Wetlands the Clean Water Act Regulates
RFF University Fellow Hannah Druckenmiller coauthored this study, which used a deep learning model to find that Supreme Court and White House rules offer dramatically different Clean Water Act regulation.
Press Release — Oct 3, 2023
RFF Introduces Six New University Fellows
The new university fellows will join a program designed to establish close working relationships between Resources for the Future and outstanding scholars in the academic community.
Journal Article — Jan 25, 2024
Machine Learning Predicts Which Rivers, Streams, and Wetlands the Clean Water Act Regulates
RFF University Fellow Hannah Druckenmiller coauthored this study, which used a deep learning model to find that Supreme Court and White House rules offer dramatically different Clean Water Act regulation.
Testimony and Public Comments — Sep 12, 2023
Comments on the National Strategy for a Sustainable Ocean Economy
This comment to the White House Office of Science and Technology Policy responds to a request for information on the National Strategy for a Sustainable Ocean Economy.
Data Tool — May 10, 2023
Weather Variability Explorer
Explore a database of decision-relevant weather variability indicators developed by Resources for the Future.
Working Paper — Apr 11, 2023
Opportunities for Increasing the Impact of NASA’s Earth Observations along Environmental Justice Dimensions
This working paper outlines ways that NASA can use its data products to promote environmental justice and overcome the barriers faced in the use of satellite data to influence decisionmaking.
Resources Radio — Mar 19, 2024
Mapping Waters of the United States Using New Tools, with Simon Greenhill and Hannah Druckenmiller
Simon Greenhill and Hannah Druckenmiller discuss a new machine learning model that can predict which rivers, streams, wetlands, and other waterways are regulated under the Clean Water Act according to different definitions of water bodies.
Common Resources — Jan 31, 2024
White House Rule on Clean Water Act in 2020 Dramatically Deregulated Waters of the United States
Machine learning can help reveal the complicated designation of which US waters are protected—or not—under various interpretations of the Clean Water Act.
Common Resources — May 10, 2023
Presenting RFF Data Commons: A Way to Tell Accessible Stories with Data
A new platform from Google and Resources for the Future makes a wealth of data sets accessible with minimal fuss. Meet RFF Data Commons.
In Focus — Mar 10, 2023
In Focus: Regulating the Waters of the United States
This video shares insights on the recent history of the “Waters of the United States” rule and why the definition of “Waters of the United States” continues to be controversial, with RFF Fellow Hannah Druckenmiller.
Press Release — Oct 3, 2023
RFF Introduces Six New University Fellows
The new university fellows will join a program designed to establish close working relationships between Resources for the Future and outstanding scholars in the academic community.
Media Highlight — Dec 15, 2022
Scientific American: "How Water Cycles Can Help Prevent Disastrous Floods and Droughts"
A journal article coauthored by Fellow Hannah Druckenmiller on the economic benefits of wetlands is covered in this story by Scientific American.
Media Highlight — Dec 5, 2022
Outrider: "Is a River Infrastructure? Experts Say the US is Rediscovering the Value of Natural Systems"
A story about the importance of riverine ecosystem services extensively quotes Fellow Hannah Druckenmiller.
Media Highlight — Nov 16, 2022
Nature: "Smarter Ways with Water"
An article in Nature Magazine about our relationship with water quotes RFF Fellow Hannah Druckenmiller and cites her work on the economic value of wetlands.