This paper builds a theory of trust based on informal contract enforcement in social networks. In our model, network connections between individuals can be used as social collateral to secure informal borrowing. We de ne network-based trust as the highest amount one agent can borrow from another agent, and derive a reduced-form expression for this quantity which we then use in three applications. (1) We predict that dense networks generate bonding social capital that allows transacting valuable assets, while loose networks create bridging social capital that improves access to cheap favors like information. (2) For job recommendation networks, we show that strong ties between employers and trusted recommenders reduce asymmetric information about the qualityof job candidates. (3) Using data from Peru, we show empirically that network-based trust predicts informal borrowing, and we structurally estimate and test our model.
Program to visualize/calculate trust flow