• “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  Funded by the Centre for the Study of African Economies, University of Oxford. 

2023 Econ Job Market Best Paper Award by the UniCredit Foundation and European Economic Association.

Coverage: VoxDev,  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 (scheduled); CSAE Conference, Oxford (scheduled); 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? Experimental Evidence from Schools in Pakistan'' with Minahil Asim and Ronak Jain (Submitted) Funded by JPAL Post Primary Education Grant (see JPAL Project Page), and RISE.  

We study the effect of communicating student-specific teacher expectations on academic performance. We randomize whether students (a) receive high-performance expectations, (b) are additionally paired with a classmate for encouragement, (c) receive information about past performance, or (d) receive no message. Expectations increase math scores by 0.19 standard deviations, with especially large effects among students who randomly received ambitious expectations and were predicted to perform poorly. Information provision has comparably large effects (0.16 standard deviations), particularly in schools with low parental literacy. However, pairing students only improves scores when peers have similar characteristics. Our findings highlight low-cost, sustainable ways of leveraging teachers to improve performance. 

• "Can Network Ties Help Facilitate Female Entrepreneurship?" with Juni Singh 

Despite many skills and entrepreneurship programs, the gender gap in entrepreneurial activities is high in developing countries. This paper focuses on bridging this gap by studying the role of peers in facilitating entrepreneurial growth for women. Peers provide direct benefits in terms of motivation, skills, and information and indirect benefits in providing access to a wider social network. Through an RCT, we vary if women attend a three-day training program with a randomly matched peer in the network versus alone and whether they attend an additional module in which the indirect value of their matched peer is made salient to them and they are encouraged to pool their network contacts. We measure the impact of the training on outcomes immediately and one year later. While the training significantly improves pro-business outcomes, pairing matters only when the individual is paired with a close friend, and more so if this friend is central in the network. Motivation and the possibility to interact in the future are the main mechanisms that drive the results. Making the indirect value of the network more salient only has modest positive effects. 

• “Spatial Inequality and Informality in Kenya’s Firm Network"  with Verena Wiedemann, Peter Wankuru Chacha, and Benard Kipyegon Kirui (Draft available upon request)

This paper leverages transaction-level tax records to study spatial patterns of domestic firm-to-firm trade in Kenya and explores how these may be shaped by the presence of an unobserved informal sector. First, we document stylised facts about formal firms in this setting, revealing a high degree of spatial concentration in the production network. Then, using data from the population census and national accounts, we show that informality is particularly prevalent in downstream economic activities and smaller regional markets. We structurally estimate a network formation model and find that accounting for informal firms in a counterfactual network increases the outdegree of firms in (i) regions with the highest levels of informal activity and (ii) regional and national trading hubs. Further, we find that the higher the informality in a sector and region, the more we underestimate its vulnerability to shocks. 

• "Impact of a Government-led Mental Health Intervention on Teaching Practices and Student Outcomes" with Preetham Rodrigues. (Fieldwork Ongoing)

We are working with public schools across 34 districts in Maharashtra, India to study how a government-mandated mental health training for teachers affects teaching practices, teacher beliefs about the education production function, student test scores, beliefs about own ability, and mental well being. The training involves the implementation of modules around student emotional well-being. We will study the impact of this training on various tradeoffs that teachers face regularly between student academic performance at the cost of work-induced stress, sociability with peers at the cost of academic effort, and course understanding at the cost of syllabus completion. Further, we will analyse the impact of the intervention on student academic performance, non-cognitive outcomes, and engagement with their social networks.

• “Network Dynamics of Temporary Migration” 

I show that interventions promoting rural-urban migration can have heterogeneous impacts on agents in different network positions. I develop a model in which agents in rural social networks exchange favours to facilitate the flow of goods and information and decide whether to temporarily migrate depending on their expected benefits. I derive each agent’s decision to migrate and their preferences over the migration decisions of others as a function of their network position. I find that agents who lie on more shortest paths are less likely to migrate and prefer lower average migration in the network. Next, I show that decisions to migrate can be strategic complements or substitutes for different agents. Finally, I use data on social networks in Indian villages and find that decisions to work outside the village are correlated with the network measure predicted by the model, and these decisions exhibit positive peer effects.