Entrepreneurs, particularly in the developing world, often hire from their networks: friends, family, and resulting referrals. Network hiring has two benefits, documented extensively in the empirical literature: entrepreneurs know more about the ability of their network (and indeed they are...

Formal financial institutions can have far-reaching and long-lasting impacts on informal lending and information networks. We first study 75 villages in Karnataka, 43 of which were exposed to microfinance after we first collected detailed network data. Networks shrink more in exposed villages....

Agents often use noisy signals from their neighbors to update their beliefs about a state of the world. The effectiveness of social learning relies on the details of how agents aggregate information from others. There are two prominent models of information aggregation in networks: (1) Bayesian...

In 30 villages, we randomly assign monitors to a subset of savers. An average monitor increases total savings by 35%. Increasing the monitor's network centrality by one standard deviation increases savings by 14%, and increasing proximity from social distance three to two increases savings by 16%

Can we identify the members of a community who are best- placed to diffuse information simply by asking a random sample of individuals? We show that boundedly-rational individuals can, simply by tracking sources of gossip, identify those who are most central in a network according to "diffusion...

We define a general class of network formation models, Statistical Exponential Random Graph Models (SERGMs), that nest standard exponential random graph models (ERGMs) as a special case. We provide the first general results on when these models' (including ERGMs) parameters estimated from the...

Absence of well-functioning formal institutions leads to reliance on social networks to enforce informal contracts. Social ties may aid cooperation, but agents vary in network centrality, and this hierarchy may hinder cooperation. To assess the extent to which networks substitute for...

We use unique data from 600 Indonesian communities on what individuals know about the poverty status of others to study how network structure influences information aggregation. We develop a model of semi-Bayesian learning on networks, which we structurally estimate using within-village data....

Social network data is often prohibitively expensive to collect, limiting empirical network research. Typical economic network mapping requires (1) enumerating a census, (2) eliciting the names of all network links for each individual, (3) matching the list of social connections to the census,...