Research

Job Market Paper

"The Professional Costs of Speech Sanctioning Events: Evidence from Academia" with Lorenzo Palladini

Steven Klepper Award for Best Young Scholar Paper DRUID 2024
Nominated for the 2026 SMS Conference Best PhD Paper Prize (October 2026)
Competitive research fellowships for this research:

Institute for Humane Studies Research Award Fellowship (2024)
Institute for Humane Studies Junior Fellowship (2026)
Scholars at Risk Academic Freedom Fellowship (2026)

Summary: How do organizations respond when an employee is publicly sanctioned for speech? Using a novel dataset of U.S.-based scholars and a staggered difference-in-differences design, we find that sanctioned scholars publish approximately 20% fewer papers and receive 4.8% fewer citations to their prior work. Their close prior coauthors also publish 12.5% fewer papers. Citation declines are concentrated among prior coauthors and same-institution colleagues and persist when the contested speech falls outside the scholar’s area of expertise. These patterns are consistent with professional distancing and show how reputational shocks propagate through scientific teams and organizations.

Case Studies

"Harvard Business School Case 625-048, August 2024 "Managing Science: Perspectives from Postdocs" with Kyle Myers (Harvard Business School), Rem Koning (Harvard Business School), Solène Delecourt (Berkeley Haas), and Katelyn Cranney (Stanford).

Publications

"When Government Shuts Down Science: When Government Shuts Down Science: Evidence from U.S. Antarctic Research" with Christian Helmers (Santa Clara) Accepted and Forthcoming at Research Policy. Media Coverage: Nature

Summary: Can brief political disruptions have lasting effects on scientific production? Exploiting the 2013 U.S. federal government shutdown in a difference-in-differences design, we find that affected scientists’ subsequent publication output fell by approximately 11%. Although researchers partially adapted by changing their collaboration patterns and reallocating effort, these adjustments were insufficient to offset the loss. The findings show that even brief disruptions can generate persistent declines in knowledge production when research depends on time-sensitive, geographically fixed, and difficult-to-substitute inputs.

Working Papers

"Benchmarking the Future of Work: Mapping AI Progress to Occupational Exposure" with Jake Prokopets.

Summary: AI benchmarks measure what models can do, but not where those capabilities will matter economically. This paper reinterprets computer-science benchmarks - the technical scoreboards of AI progress - as economic indicators of where frontier capabilities are becoming relevant to work. We construct the Benchmark-Anchored Index of Occupational Exposure by mapping time-stamped benchmark performance to O*NET abilities and occupations. The index also predicts subsequent patterns of realized AI use measured by Anthropic’s Economic Index, providing a forward-looking signal of where technological pressure is building and where organizations may need to redesign workflows and invest in complementary capabilities.

"Does Politics Permeate Science? Evidence from a Field Experiment on Political Bias in Academic Opportunity" with Jessica Khan (Northwest Florida State College). Draft available on request.

Presented at the NBER Investments in Early Career Scientists 2026

Summary: Critics frequently allege political discrimination in academia, but does it actually shape access to academic opportunities? Across three audit experiments involving approximately 10,000 U.S. professors, we randomly vary the political orientation signaled by fictitious prospective students. We find no evidence of differential treatment among STEM professors, but document bias against conservative applicants in the social sciences and humanities. The findings show that political gatekeeping is field-specific and informs current debates over federal funding interventions in higher education: broad university-wide funding cuts may not be warranted.

"From Ancient Centers to Modern Capitals: The Influence of Historic Civilizational Hubs on the Spatial Distribution of Population and Political Power" with Justin Cook (Tulane) and Raymond Kim (Westmont College).

Summary: How does historical political centrality shape the contemporary distribution of population and economic activity? Using a novel geolocalized dataset of approximately 500 civilizations spanning 3200 BCE to 1500 CE, we find that regions closer to polity centers accumulated higher population densities, including in panel specifications that exploit within-cell changes in centrality induced by shifting historical borders. Evidence from Roman roads suggests that public investment was disproportionately concentrated near civilizational cores. Historical centrality also predicts the location of modern national capitals and contemporary economic activity, revealing persistent effects on political and economic geography.

"Do Women Ask For Less? The Gender Ask Gap in Science" with Valentina Tartari, H.C. Kongsted, Astrid Ulv Thomsen, and Lorenzo Palladini (Stockholm School of Economics and Copenhagen Business School). Draft available on request.

Summary: Do gender disparities in scientific funding emerge before proposals are evaluated? Using the universe of approximately 8,600 funded and unfunded applications submitted to two large European science funders, we find that female principal investigators request 5.0–5.4% less funding than comparable male applicants, accounting for approximately 70–80% of the corresponding gap in awarded funding. Smaller requests do not increase the probability of success, suggesting that the gap does not reflect strategic under-requesting. The gap persists in team-based applications, even when female PIs apply with male co-applicants, although mixed-gender teams partially attenuate it. It is concentrated among early-career and first-time applicants and disappears with repeated applications, consistent with learning and information frictions in how researchers calibrate the resources needed to pursue their ideas.

"WAGE-Bench: Measuring the Economic Value of AI in Real Work" Preliminary draft, working on the field experiment version of this.

Summary: This project develops an economically interpretable measure of the value of AI assistance in real work. Using an incentive-compatible mechanism, we elicit workers’ willingness to accept compensation for completing realistic tasks with and without AI assistance. The resulting measure captures how AI changes the perceived cost of work - including time, effort, trust, and verification burden - and can be compared across models, tasks, occupations, and worker populations.

"CentaurBench: Benchmarking LLM Assistance on Real-World Work" with Kenny Wongchamcharoen, Min Min Fong, and Abhishek Nagaraj (Berkeley Haas)

Summary: Are the large language models that perform best autonomously also the most effective at assisting workers? Across seven economically grounded tasks, we compare models completing work independently with models providing guidance to a fixed lower-capacity worker model. Automation and augmentation rankings differ substantially, and assistance does not consistently improve performance, showing that organizations should evaluate AI models according to the specific roles and tasks in which they will be deployed.

Early Work in Progress

"The Impact of AI on Science: Evidence from an RCT" with Rem Koning (Harvard Business School)

"Tasks in the Age of Automation" with Abhishek Nagaraj (Berkeley Haas) and Isaac Robinson (Mercor)

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