Friends and acquaintances rely on one another for many important economic needs: They informally borrow and lend. They share information about jobs, consumer products, and government programs. They offer and seek help with emergencies and daily tasks such as childcare. These interactions are all quite different, and so the partners who are best for each need may differ. Nonetheless, in practice, people layer many of their relationships. For example, they rely on the same friends for loans and for information about new products or job opportunities. The PIs investigate how people choose which relationships to layer, and how this affects their welfare. How much of layering is explained simply by the compatibility of friends across many different activities, and how much is due to the fact that bundled relationships work better? How does the network used for daily favor-trading shape who talks to whom, and how information flows in society? Are wealthier individuals able to get more useful information because their networks are less constrained by meeting daily needs, especially financial ones? How does this affect job search and inequality?

The PIs develop first foundational theory for multi-relational network formation, which is not covered by existing models. They present four reasons for the layering of different kinds of connections on top of each other: (1) cost savings, (2) synergies, (3) coordination, and (4) compatibility. They then examine some of the implications of these theories, propose empirical tests of the resulting models, and conduct preliminary analysis using existing and new field data. The second part of the project focuses on a particularly policy-relevant aspect of multi-relational networks. Wherever access to financial services is limited - in the developing world and also in many communities in the developed world - a fundamental network that underlies the formation of many others is that of risk-sharing: informal borrowing and lending, for emergencies and for ordinary activities. Due to layering, the risk-sharing network becomes a crucial driver of the social structure of a community, including, for example, its informational links. Risk-sharing therefore influences outcomes well beyond mutual insurance, such as who is informed about various topics and how people form opinions. Poverty traps caused by limited access to financial services affect much more than investment and consumption behavior, and can exacerbate inequality by biasing access to information. For instance, if people only obtain information about the availability of jobs from their unemployed neighbors, they will find it harder to search for a job. Thus, changes in the motives to share risk within a network - say, through the availability of crop insurance, bank accounts, or other means of income smoothing - has profound implications for how a society is able to process information. Financial burdens that people face can bias their networks in ways that lead to inefficient social learning; freeing individuals from having to share risk may result in more efficient information networks. The PIs will be developing theory that speaks to these issues and performing field and lab experiments to test the theories and potential policies for improvement. A final component of the proposed research digs deeper into information networks, whose functioning is critical to the questions raised above. In this part of the project the PIs plan to examine a tension between motives to share information and motives to conceal it. A person may wish to tell her friends about a valuable opportunity, such as a new insurance program. However, if only a limited number of people can benefit from a piece of information, for instance regarding a job opening, a person may not want it to spread too broadly. This has major implications for information-sharing, but there is very little theoretical or empirical study of these issues. The PIs propose theoretical investigations and field experiments to understand how the nature of a new economic opportunity - e.g., whether it is rivalrous - affects its diffusion. In terms of empirical work, the proposed research will collect network data across a large set of rural communities and conduct several field and lab experiments to investigate these topics.

National Science Foundation (NSF)
Division of Social and Economic Sciences (SES)
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Kwabena Gyimah-Brempong
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National Bureau of Economic Research Inc
United States
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