THE IMPORTANCE OF SOCIAL NETWORKS IN DETERMINING THE UPTAKE OF MICROFINANCE

Principal Investigators: Abhijit Banerjee (MIT), Esther Duflo (MIT)
Research Team: Manaswini Rao
LEAD Centre: Centre for Microfinance (CMF)
Focus Area: Credit, Savings
Project Geography: Karnataka
Partner: Bharatha Swamukti Samsthe (BSS)
Status: Ongoing

Background:

A major concern of all MFIs is how best to introduce microfinance into new communities. Indeed, the chosen strategy may be critical to the rate at which loans are taken up, not to mention the type of borrower the institution attracts. Is it important, for example, to focus on socially influential individuals, who have the connections to recommend microfinance, or to target less wellconnected, marginalized people, who may have a stronger stake in championing the program? Would a strategy that concentrates on one key individual in a group mean better repayment, or would it be more effective to treat all group members equally, given that there is no central group member? A large theoretical literature informs these questions, as microfinance may be thought of as an innovation, or something newly introduced to the community. However, there are relatively few empirical studies that show how a particular innovation diffuses through the various social networks in the community, and how the characteristics of these networks are important for its diffusion.

The objective of this study is therefore to understand how social networks are important to the spread of microfinance. The study is a survey of 50 semi-urban villages located near Bangalore, in which the microfinance institution BSS is planning to set up centres. GPS technology will map out the geography of the village, while interviews with those women who meet BSS’s basic loan criteria, as well as with adult family members, will allow for a mapping of the various existing social networks of the village. After the survey of the villages is complete, and BSS has entered, CMF will use the BSS data on loan uptake over time to identify how individuals decide whether to join or not and with whom to join. It will also reveal how these decisions depend on their social network position and the behavior of those with whom they have links.