Noor Sethi
Agricultural and Resource Economics | UC Berkeley
Agricultural and Resource Economics | UC Berkeley
I am a PhD candidate in Agricultural and Resource Economics at UC Berkeley, completing my degree in spring 2026 and seeking research and policy positions.
My research focuses on how governments can better target the poor. I study
whether machine learning methods improve the accuracy of proxy means testing for cash transfer programs; and
how programs should be designed when households respond strategically to eligibility criteria.
My work draws on household survey data from India and combines econometric and computational methods.
Prior to joining the UC Berkeley community, I studied economics and mathematics at Smith College, and I worked as a research analyst at Innovations for Poverty Action.
I welcome opportunities to connect- feel free to reach out.
"Hit or Miss: Targeting the Poor (Better)"
15–20% improvement in poverty targeting accuracy by replacing OLS-based proxy means testing with non-parametric ML
k-Nearest Neighbors achieves best performance; welfare gains are largest under budget constraints and inequality-averse utility
Error minimization and welfare maximization require different targeting thresholds with direct implications for policymakers
"Hit or Miss(ing) Assets: Optimal Targeting Thresholds Under Strategic Behavior"
Develops a framework for optimal government threshold-setting when households strategically conceal assets to qualify for transfers
Optimal threshold when income is unobserved (Rs. 13,200) corresponds to 65% coverage vs. 30% when perfectly observed
Higher thresholds reduce misreporting incentives through smaller transfers, lower marginal utility, and harder-to-hide assets
"Born at the Right Time?" (with Ann Harrison and Laura Kray) [link] [news]
Under review
Documents 33% reduction in gender wage gap among MBAs over 20 years; finds gaps now emerge immediately at career entry
Identifies low-cost childcare availability and work flexibility as primary remaining determinants of persistent disparities
Based on 30 years of survey data from a large public university business school
The following research emerged from projects on which I served as a research assistant.
"Graduating the Ultra Poor in Ethiopia" (Dean Karlan & Nathanael Goldberg) [link]
Found 18% consumption gains and 68% higher asset values one year after program exit; estimated benefits outweigh costs 2.6-to-1
Part of a six-country RCT testing whether comprehensive "big push" interventions enable sustainable escape from extreme poverty
My contribution: programmed survey in SurveyCTO
"Evaluation of Combined Financial Incentives and Deposit Contract Intervention for Smoking Cessation" (Dean Karlan et al.) [link]
Financial incentives and deposit contracts produced positive but imprecisely estimated effects on smoking cessation among Medicaid enrollees
Findings inform the design of commitment contract programs for low-to-moderate income populations
My contribution: collected data in the field (clinics across Connecticut), designed data pipeline and monitored incoming data for inconsistencies
"Twenty Year Economic Impacts of Deworming" (Edward Miguel et al.) [link]
Found 14% consumption gains and 13% earnings gains from childhood deworming
Findings inform cost-effectiveness analyses for global health program prioritization
My contribution: collected survey data in the field (Busia, Kenya), cleaned and analyzed data in R
"More COPS, More Fatalities?" (Rebecca Goldstein)
Applied regression discontinuity design to show additional police hiring increases officer-involved fatalities
Findings contributed to national policy debate on federal police funding
My contribution: cleaned and analyzed data in Stata
In other words: the people, places, and chance adventures that bend and sway our minds, shape what we study and how we write about it, but rarely make it past the acknowledgements page.
Busia, Kenya | Innovations for Poverty Action
Dharamshala, India | Chinmaya Organization for Rural Development
Córdoba, Argentina | Ciudadanos 365
Workshop leader, Spring 2020, Fall 2021, Spring 2021, & Fall 2022 | UC Berkeley
Workshop participant, Fall 2020 | UC Berkeley