“Learning in Networks with Idiosyncratic Agents” (Games and Economic Behaviour, 2024) Twitter thread
Individuals update their beliefs and respond to new information in idiosyncratic ways. I show that an individual’s idiosyncrasies such as under-reaction, over-reaction, or frustration can have spillover effects and adversely affect the long run beliefs of society. I derive sufficient conditions for convergence of beliefs for all possible networks of agents with heterogeneous idiosyncrasies. Beliefs converge if the magnitude of over-reaction and frustration in any agent's network neighbourhood is below a threshold determined by how much they trust their own private signals. I find that the absence of disproportionately influential agents is not sufficient to ensure the accuracy of long-run beliefs if learning idiosyncrasies also grow with the network. Finally, I show that agent under-reaction can partition the network, create bottlenecks, and delay convergence. Simulations on artificial and Indian village networks validate the results.
"Silent Networks: The Role of Inaccurate Beliefs in Reducing Useful Social Interactions" with Ronak Jain
2023 Econ Job Market Best Paper Award by the UniCredit Foundation and European Economic Association.
Can pessimistic beliefs about social norms create “silent” networks, where individuals rarely seek support despite benefits? A field experiment with informal workers shows that belief correction increases demand for social support by reducing perceived reputational costs. We use a network model to explain how misperceptions can arise and trap communities in a low-interaction equilibrium. Structural estimation predicts that the induced shift is too small to escape this equilibrium. Accordingly, two years later, those exposed to the treatment hold more optimistic beliefs, but below the true level conveyed. Counterfactuals show that stronger policies are required for persistence, though belief correction can increase the demand and funding to support them.
Coverage: VoxDev (2025), VoxDev (2024), Ideas of India Podcast at the Mercatus Centre. Spotify Link.
Presentations: (2024) Workshop on Networks and Development, Naples; CSAE Conference, Oxford; PacDev, Stanford. (2023) European Winter Meeting of the Econometric Society, Manchester; NEUDC, Harvard; CEPR-TCD TIME Conference on Economic Development, Trinity College Dublin; OxDev, Oxford ; CSAE Research Workshop, Oxford; Informal Presentation at the King Center of Global Development, Stanford; Presentation to the Communities Project Team, Stanford; Interface of Theory and Experiments at the Economics Research Jamboree, Oxford.
"Great Expectations? Leveraging Teachers to Improve Student Performance'' with Minahil Asim and Ronak Jain
Funded by JPAL Post Primary Education Grant (see JPAL Project Page), and RISE. Coverage: VoxDev (2024)
Do high teacher expectations improve student performance? Theoretically, expectations can motivate students by raising aspirations or discourage them if perceived as unrealistic or evoking unfavorable peer comparisons. To causally identify their effects and unpack mechanisms, we randomize whether students receive expectations framed as attainable or ambitious, are additionally paired with a classmate for encouragement, or only receive information about past performance. Communicating expectations increases math scores by 0.21σ, particularly for students receiving ambitious goals or predicted to perform poorly. Information about past performance has comparable effects (0.18σ), as students interpret it as attention and encouragement from the teacher. Pairing only helps when students are similar, indicating that interpersonal comparisons negatively affect motivation. Although students with large gaps between expectations and baseline performance show sustained gains 12–18 months later, the effects of expectations and information remain statistically indistinguishable. Overall, our findings highlight that signals of personalized teacher attention—through communicating expectations or performance—are a low-cost, effective input in the education production function.
“Spatial Inequality and Informality in Kenya’s Firm Network" with Verena Wiedemann, Peter Wankuru Chacha, and Benard Kipyegon Kirui | World Bank Working Paper Series
The spatial configuration of domestic supply chains plays a crucial role in the transmission of shocks. This paper investigates the representativeness of formal firm-to-firm trade data in capturing overall domestic trade patterns in Kenya — a context with a high prevalence of informal economic activity. We first document a series of stylized facts and show that informal economic activity is not randomly distributed across space and sectors, with a higher incidence of informality in downstream sectors and smaller regional markets. We then link granular transaction-level data on formal firms with data on informal economic activity to estimate a structural model and predict a counterfactual network that accounts for informal firms. We find that formal sector data overstates the spatial concentration of aggregate trade flows and under accounts for trade within regions and across regions with stronger social ties. Additionally, the higher the informality in a sector and region, the more we underestimate its vulnerability to domestic output shocks and overestimate its vulnerability to import shocks.
We implement a randomized entrepreneurship program that induces peer interactions to study the mechanisms underlying peer effects -- how they vary with network position, evolve over time, and can be engineered. We find that socially close and more connected peers generate short-term gains, while socially close but less connected peers generate long-term gains. This is driven by motivation from well-connected peers in the short term and ease of collaboration with less-connected peers in the longer term. We estimate peer effects and find that a 1σ increase in peers’ entrepreneurial outcome increases an individual’s future outcome by 0.4σ, but the effect declines by 0.06–0.08σ for each additional connection of the peer. Simulations show that pairing based on network position can be feasibly leveraged to increase treatment effects. Finally, we randomize a “connections” treatment in which peers share their network contacts. Despite network sparsity, sharing contacts does not generate additional gains and is concentrated within existing social groups, showing that peer effects are difficult to engineer in settings with high homophily.
"Parental Involvement in Education and Children’s Human Capital Formation" with Sonya Krutikova, Abu Siddique, Michael Vlassopoulos and Yves Zenou. (Fieldwork Completed)
"Social Learning through Meal Sharing" with Juni Singh. (Fieldwork Ongoing)
"Social Connections among the Elderly" with Alison Andrew, Anandi Mani, and Sanchari Roy. (Fieldwork Ongoing)
"Impact of a Government-led Mental Health Intervention on Teaching Practices and Student Outcomes" with Minahil Asim and Preetham Rodrigues (Fieldwork Completed)
"Social Networks, Mental Health, and Domestic Violence" with Sonia Bhalotra and Manuela Angelucci.
"Mask Up! How Social Networks affect Adoption of Public Health Behaviours and Norms" with Dennis Egger, Aleksandra Jakubowski, and Michael Walker.