This NSF award funds new research analyzing how networks affect economic behavior. The researchers collect a unique dataset that includes detailed network and demographic data on individuals in 75 villages in South India. Forty-three of these villages participated in a microlending project, and the data includes information on the social networks in all of the villages before and after the introduction of microlending. The research team uses the data to test hypotheses about whether and how a social network changes when the participants do not need to rely on informal social borrowing/lending relationships because formal microloans are available. The team will also conduct three other studies. They will trace the information and diffusion of advice across the network, they will study how the social network affects the success of a program designed to use peer influence to encourage saving, and they want to study the role of peer networks in decisions to default on formal loans.
Broader impacts include the creation of a unique data set that is useful for researchers across the social sciences who are interested in how to model and analyze social networks. Graduate students and undergraduates are involved in the project. Finally, microfinance has been lauded as a new solution to problems facing poor people in developing countries. However, recent evidence makes it clear that social networks play a key role in the success or failure of microlending programs. Understanding this role is key for the design of new microlending policies and products.
