• “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.

Coverage: VoxDev (2025), VoxDev (2024),  Ideas of India Podcast at the Mercatus Centre. Spotify Link. 

Inaccurate beliefs about social norms can reduce useful social interactions and adversely affect an individual’s ability to deal with negative shocks. We implement a randomized controlled trial with low-income workers in urban India who lack access to formal financial and healthcare support. We find that the majority of individuals underestimate their community’s willingness to engage in dialogue around financial and mental health concerns. Belief correction leads to a large increase in the demand for network-based assistance. We show that the effects are driven by a reduction in the perceived costs of violating social norms arising due to concerns around reputation and insensitivity. We structurally estimate a network diffusion model and predict that our belief correction intervention will not lead to a shift in equilibrium engagement. Consistent with this, 2 years later, we find that the average beliefs of those exposed to the intervention are significantly more optimistic but still lower than the information delivered in the experiment. We compute the strength of counterfactual interventions needed to generate a sustained effect and find that belief correction can be used to generate both the demand and funding for such policies.

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)

We study how teacher expectations affect academic performance by randomizing whether students (a) receive expectations framed as attainable or ambitious, (b) are additionally paired with a classmate, (c) receive past performance information, or (d) receive no message. Expectations increase math scores by 0.21σ, particularly for those receiving ambitious goals or predicted to perform poorly. Information has comparable effects (0.18σ), especially in low-literacy settings. Pairing only helps when students are similar. Students with large gaps between expectations and baseline performance show sustained gains 12–18 months later. Findings highlight teacher-student communication as an 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.

• "Heterogeneous Peer Effects in Social Networks: Evidence from an Entrepreneurship Experiment" with Juni Singh 

We evaluate the impacts of a randomized entrepreneurship training program to show that peer effects vary systematically with network position, evolve over time, and cannot be easily engineered. We find that socially close and more connected peers generate short-term gains, whereas 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’ outcome increases an individual’s future outcome by 0.3σ, but the effect declines by 0.06–0.07σ 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 module” in which paired trainees share their network contacts. Despite network sparsity, sharing contacts does not generate additional gains and is concentrated within caste, suggesting that peer effects can be 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" (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.