Working Papers

Expected Discrimination and Job Search, with Ieda Matavelli and Fernando Secco. Conditionally Accepted, AER.

Abstract | Paper | World Bank Blog, Nexo

We study how expected discrimination affects job applications and interview performance in three field experiments with 2,167 jobseekers living in Brazilian favelas (urban slums). We focus on antifavela discrimination, which 87% of jobseekers overestimate. Randomizing expected address visibility---or providing information about discrimination in callbacks---does not affect average application rates or interview attendance. However, expecting interviewers to know one's favela address reduces interview performance by 0.13SD, even though interviewers are in fact blind to addresses. Expected discrimination can thus affect labor market matching, especially in hiring processes that involve face-to-face interviews.

Virtue Signals, with Matt Lowe. Revise and Resubmit, JEEA.

Abstract | Paper

We study whether tweets about racial justice predict costly related behaviors. Academics that tweet about racial justice are more likely to favor minority students in an audit experiment, receive higher teaching ratings, work with more Black co-authors, and are more likely to subsequently leave Twitter. Non-academics that tweet about racial justice make larger private donations towards racial justice efforts. However, three pieces of evidence suggest that higher returns to tweeting reduce the predictive value of racial justice tweets. First, tweets became almost completely uninformative during the aftermath of the murder of George Floyd, when more people were tweeting about racial justice. Second, the informativeness of tweets is driven by low-visibility tweet types, like retweets. Third, racial justice retweets are somewhat less informative of donation behavior than private statements of support. Finally, we find that roughly half of surveyed graduate students are overly cynical, believing tweets to be close to uninformative.

Where Does Top Talent Go to College? Global Talent Allocation and Its Consequences, with Ruchir Agarwal and Patrick Gaule. Available upon request.

Abstract

The world's highest-potential students may be unable to attend leading universities, which concentrate in a handful of countries. Such "undermatch" can be a problem if student potential and university quality are complements in the creation of social value. To study the allocation of top global talent to universities and its consequences, we assemble undergraduate and career histories for 11,424 International Mathematical Olympiad participants. We present three main findings. First, we estimate that 31% (48%) of recent medalists attend a top-10 (top-50) university, with substantial geographical heterogeneity: the main predictor of whether a medalist attends a top university is whether their origin country has one. Second, the undermatch appears consequential. Conditional on individual characteristics including initial math ability, attending a better-ranked university predicts a higher probability of earning top-10 PhD degrees, winning major scientific prizes, and working in a top tech firm. Sensitivity analyses suggest that unobservable factors would have to be over three times more relevant than initial math ability to overturn those associations. Third, we present an evidence-based discussion of the reasons behind the undermatch and of which policies could be most effective in ensuring that the world's best students have a shot at attending the best universities.

The Missing Nobels: Mapping the Landscape of Prestigious Scientific Prizes, with Ruchir Agarwal and Patrick Gaule. Revise and Resubmit, PLOS ONE.

Abstract | Paper

Prestigious recognition prizes, like the Nobel Prizes, can shape scientists' career decisions and how science is seen. Yet the landscape of such prizes is not well understood. We screen roughly 2,700 international scientific prizes and rank the 99 most prestigious using a novel prestige index. Recognition is unevenly distributed across fields: physics, life sciences, and mathematics are heavily recognized relative to field size, while computer science, engineering, psychology, and the social sciences are under-served. Only three of the 99 prizes target early-career scientists.

Work in Progress

The Effects of Testing on Talent Development, with Kim Kiekens (SPRING-STOF)

Can a Universal Math Competition Create Talent? Evidence from Brazil

Women's Cognitive Load and Labor Market Outcomes in Brazil, with Ieda Matavelli, Beatriz Marcoje, and Jamie McCasland

International Olympiad Competitors as Tech Founders, with Ruchir Agarwal, Patrick Gaule, João Francisco Gomes Marques, and Thais Harumi Hanai Takeuchi

Frontier AI and Early-Career Scientific Production

Agent-Built Research

Presentation and writing done mostly by LLMs. Please assign trust accordingly.

Social Media and Scientific Productivity | Data explorer

Abstract

How does social media use affect scientific productivity? While social media may reduce research time, it could also enhance productivity by facilitating remote and interdisciplinary collaborations, especially for researchers with initially small collaboration networks. I use a matched differences-in-differences approach to explore the effect of joining Twitter on scientific productivity across US academia. My sample includes 28,000 research-active academics from top-150 US institutions, in all fields of study, matched to OpenAlex publication histories via custom author-ID disambiguation, gender classification by name, and institution linking. I estimate the causal effect of joining Twitter on the number and quality of publications, general citations, citations to papers published before joining Twitter, the geographic distance and disciplinary breadth of co-authorship networks, and horizontal and vertical job transitions.

Resting Papers and Projects

Female Pradhan Autonomy

Abstract

Many countries have implemented electoral gender quotas to improve representation in public decision-making. At the same time, verifying whether such policies are successful -- and not just generating figureheads for male family members, for instance -- is hard, especially at the local level. I propose a novel and scalable measure of female leader autonomy for village leaders in India: whether the female leader owns the phone number used to communicate with higher levels of government. I then explore whether past quotas for females lead to more autonomy and whether autonomy predicts public policy outcomes.

Dynamic Coordination with Network Externalities: Procrastination Can Be Efficient

Abstract | Paper

How does present bias affect welfare when agents want to coordinate over time? To answer that, I analyze a dynamic coordination model under quasi-hyperbolic discounting, documenting a novel mechanism through which present bias can be adaptive. The key trade-off for agents in dynamic coordination models is whether to follow a currently-popular standard (receiving substantial network externalities from other current users) or to adopt a new standard with a higher intrinsic quality, hoping that others will follow. Guimarães and Pereira (2016) showed that exponential discounters begin adopting the new standard when its quality is too low to justify the transition costs, since an early adopter does not account for the negative externality caused on those who stay in the old standard. This paper shows that present bias can act as kludge, since it makes agents overweight their individual transition costs, shifting behavior in the same direction that the planner would suggest.