Research

How does rural productivity affect cities? I use Indonesia's Transmigration Program, which resettled over two million people to newly established villages in the 1980s. The haphazard rollout of the policy generated plausibly exogenous variation in agro-climatic similarity between migrants' places of origin and destinations, with higher similarity resulting in more productive villages. Cities surrounded by more productive villages undergo sectoral employment changes without much population growth: modern-sector employment expands while the remaining peri-urban agriculture contracts. New arrivals cannot account for the shift, and settlers largely stay in their villages, suggesting sector switching among urban residents. The effects concentrate in cities less connected to global markets, where food expenditures fall, and non-agricultural employment grows most. In a spatial general equilibrium model, I show that the observed reallocation of urban employment out of agriculture can occur with lower levels of internal migration, but not without agricultural trade.

A single high-stakes exam decides college access in much of the world, and in many cities of the Global South gun violence is routine in the weeks students sit it. We link shootings near Rio de Janeiro schools to an administrative panel that follows students from elementary school through college, comparing school-years with a shooting shortly before Brazil's national exam (ENEM) to school-years without one. Exposure lowers math scores by about 0.05 of a standard deviation, and by 0.20 among marginal students, yet on-time college entry does not move, a fairly precise null. The composition of entry changes instead: enrollment shifts from public into private institutions, take-up of federal student aid expands, and entrants avoid flagship public universities, consistent with Brazil's threshold-based admission rules. A few days of violence leaves the level of college access intact while durably re-sorting who pays for college, in which sector, and on what timeline.

Up to one in three adults report insomnia symptoms; the burden falls hardest on the urban poor. Whether poor sleep helps keep poor people poor is untested: the one field experiment raising sleep among low-income workers added time in bed without adding quality, and found no gains in cognition, productivity, or earnings. We ask whether the constraint is instead sleep quality, and test it with Cognitive Behavioral Therapy for Insomnia (CBT-I), the clinical first-line treatment, which raises sleep efficiency while leaving sleep time roughly unchanged: any economic effect cannot come from more hours of sleep. In an experiment with nearly 300 adults with insomnia symptoms in Nairobi, we compare four weeks of lay-facilitated group CBT-I with an active control, with pre-registered endpoints spanning sleep, mental health, cognition, and economic outcomes. To our knowledge, this is the first adult randomized trial of CBT-I in sub-Saharan Africa.

We estimate the causal effect of urban employment growth on the rural economies surrounding Indian cities, asking whether villages share in the gains from urban expansion or lose their people and activity to it. We link roughly 1,500 cities, delineated by their built-up boundaries, to more than 250,000 villages, and instrument nearby urban employment growth with a shift-share design based on national industry shocks. Urban growth moves the village economy in two opposite directions: a 10-percentage-point increase in nearby urban employment growth slows village population growth while raising village employment growth by about 3.6 percentage points. The gains are concentrated in services, with no effect in manufacturing. Close to a growing city, the gains are in trade and services, consistent with demand from urban visitors. Farther away, employment gains are concentrated in resource extraction and accompanied by a shift out of farm work.

This paper investigates the role of beliefs and stigma in shaping students' use of professional mental health services at a large private university in Mexico, where services are readily accessible. In a survey experiment with 680 students, we find that nearly 50% of students in distress do not receive professional support despite high awareness and perceived effectiveness, a substantial treatment gap. We document stigmatized beliefs correlated with this gap: three-quarters of students incorrectly believe that those in distress perform worse academically and that most students going to therapy are in severe distress. An information intervention correcting these beliefs increases students' sharing of on-campus mental health resources with peers and their willingness to recommend these resources to a friend in distress, yet it lowers willingness to pay for private therapy and does not reduce self-reported therapy use six months later.

A clear understanding of community response to government decisions is crucial for policy makers and health officials during the COVID-19 pandemic. In this study, we document the determinants of implementation and compliance with stay-at-home orders in the USA, focusing on trust and social capital. Using cell phone data measuring changes in non-essential trips and average distance traveled, we find that mobility decreases significantly more in high-trust counties than in low-trust counties after the stay-at-home orders are implemented, with larger effects for more stringent orders. We also provide evidence that the estimated effect on post-order compliance is especially large for confidence in the press and governmental institutions, and relatively smaller for confidence in medicine and in science.

Models of housing market dynamics examine the spatial diffusion of price changes from an epicenter through a regional or national network of geographic units. Less common has been the study of a ripple effect of price changes within a single metropolitan area, with implications for the erosion of residential affordability. Such trends have particular salience in the Vancouver metropolitan area, the least affordable housing market in North America. Using quarterly price data from local real estate boards, we examine price changes through municipal regions from 2005-2017, a period including several externally-induced price shocks. A time lag of three months consistently exists in the communication of price shocks from an originating epicenter to other parts of the metropolitan region, with longer lags for several more distant municipalities, confirming the presence of an intra-metropolitan ripple effect.

Reproducibility efforts strengthen science by testing the reliability of published findings and promoting self-correction. Computational reproductions, whereby independent researchers reproduce the results of published studies, are an essential diagnostic tool. We reproduced original analyses and conducted robustness checks of 110 articles published in leading economics and political science journals with mandatory data- and code-sharing policies. More than 85% of published claims were computationally reproducible. In robustness checks, 72% of statistically significant estimates remained significant and in the same direction, and the median reproduced effect size was 99% of the originally published effect size. Six independent research teams then examined 12 pre-specified hypotheses about the determinants of robustness: teams with more experience found lower levels of robustness, and robustness did not correlate with author characteristics or data availability.

Large language models (LLMs) such as ChatGPT are transforming how scientists conduct and validate research, yet computational reproducibility and error detection remain expensive and labor-intensive. We experimentally test how collaboration between researchers and LLM assistants influences the reproduction of quantitative social science findings. We randomly assigned 288 researchers to 103 teams working under three conditions: human-only, AI-assisted (ChatGPT as a collaborative tool), or AI-led (ChatGPT with minimal human oversight). Teams reproduced published results from leading social science journals, detected coding errors, and proposed robustness checks. Human-only and AI-assisted teams achieved comparable reproduction rates (94% vs. 91%), and human-only teams identified more major coding errors. Both substantially outperformed AI-led teams, which achieved a 37% reproduction rate, detected fewer errors, and proposed weaker robustness checks. Expert human judgment currently remains indispensable for reliable empirical verification.

Essential public-sector workers in low- and middle-income countries (teachers, health workers, police officers) operate under chronic stress, exposure to community violence, and institutional neglect of their mental health. Burnout, anxiety, and untreated trauma are pervasive among these frontline workers, yet rigorous evidence on scalable interventions to support their wellbeing remains nearly nonexistent. This gap matters not only to the workers themselves, but also to the quality of public services they deliver. We provide experimental evidence on whether socio-emotional resilience training can improve the mental health and professional effectiveness of essential workers, focusing on public school teachers in Guatemala. We evaluate SanaMente, a trauma-informed training program that builds skills in stress recognition, emotional regulation, and supportive workplace practices, using a school-level cluster-randomized trial across 120 schools targeting 600 teachers in three municipalities in Guatemala.

We design and test a novel tutor-training intervention on a tutoring platform, with a focus on peer-group discussions. Roughly 2,000 university-student volunteer tutors lead math sessions for around 8,000 schoolchildren. By comparing Social and Emotional Learning (SEL) training with and without peer-group discussions, we isolate the role of peer connections in improving teaching, self-confidence, and communication. Pilot results indicate that students assigned to tutors who participated in peer-group discussions show larger gains in endline math scores than those whose tutors trained individually or without SEL training; tutors trained in peer groups also feel more connected and supported.

The Migrant Protection Protocols (MPP, "Remain in Mexico") required non-Mexican asylum seekers arriving at the U.S.–Mexico border to wait in Mexico during their immigration court proceedings. Using administrative case-level microdata from the Executive Office for Immigration Review covering over one million cases from 2012 to 2020, we estimate the causal effect of MPP on procedural-fairness outcomes with an event-study difference-in-differences design, comparing non-Mexican respondents, who could be placed in MPP, with exempt Mexican respondents in the four border courts that operated MPP dockets. MPP eligibility reduced legal representation by 7 to 13 percentage points, and a triple difference against other border-state court cities locates the decline specifically in MPP courts. In-absentia adjudication and removal also rose, but comparably elsewhere along the border. Access to counsel is an important and less visible margin through which border policy shapes participation in immigration court.

The most urbanized continent, Latin America lags on the economic development expected of its high urbanization rates. Across the region, I find that while industrialization and resource rents explain some variation, they are insufficient to account for exceptionally high urbanization. I present suggestive evidence that the colonial past created an urban system later conducive to "urbanization without growth."

Inequality is widely studied within and across countries, but much less is known about inequality between the leading cities of different countries. I study an international cross-section of leading cities in high- and middle-income countries and propose a measure of the gap between a major city's per capita income and its country's national average. Since 2010 most countries in the sample have been catching up with their leading cities, consistent with cities acting as engines of growth. Reading the cross-section through a structural transformation lens, and clustering cities by a principal component approach, I find convergence both between clusters of developed- and developing-country cities and within clusters of similarly developed cities. Cities growing faster in population and per capita income show a wider city-country gap, while a stronger national economy and a larger primary-sector share in city output narrow it.