Because exchange is sequential, most economic transactions require contracts, and hence efficient contract enforcement is an important part of a well-functioning economy. In advanced countries, the legal system provides low-cost contract enforcement for many transactions. However, efficient legal systems are historically recent, and absent in most developing countries. When legal contract enforcement is costly, economic actors often rely on informal arrangements that are enforced using social or business sanctions. As a result, social and economic networks play an important role in determining the informal contracts that shape economic activity.
Motivated by these observations, this project develops a theory of informal contracting in networks. The key idea is that social and business connections generate value which can be used as "social collateral" to facilitate informal contracts. Analogously with physical collateral, the threat of losing valuable connections prevents agents from acting dishonestly. The structure of the network determines the amount of social collateral available to agents, and hence social collateral constitutes one aspect of social capital that is embedded in the network of interactions. The project uses this theory to investigate 1) trust generated by the social network; 2) the functioning of informal insurance markets; and 3) the determinants of power in a society.
Relationships in the network determine how much agents can borrow from each other, leading to a computable measure of trust based on social collateral. This measure is intuitively appealing: it predicts that more connected and more homogenous networks generate higher trust, and provides foundations for many network statistics used in economics and sociology. This theory of trust also formalizes the idea that dense networks generate bonding social capital which is helpful when agents exchange valuable assets, while loose networks maximize access and hence generate bridging social capital.
In less developed countries, informal arrangements among socially connected people are often used to provide insurance against adverse shocks like unemployment or illness. The theory predicts that in networks organized by geographic proximity, such informal risk-sharing is likely to be effective, and that socially close individuals are likely to form local risk-sharing groups to jointly weather the burden of negative shocks. The project also studies the interaction between government policies and network-based insurance by exploring the network effects of development aid using data from Peru.
When there is competition for resources, people can benefit from their network position: a centrally located lender earns higher rents because more borrowers compete for his assets. This logic yields a theory of power in networks, where a negative aspect of social capital, the inequality between insiders and outsiders, can be formally investigated.
In sum, this project yields a deeper understanding of how the social network provides informal contract enforcement, which helps explain stylized facts about trust and generates new measures of social capital. The analysis yields results of interest to policymakers about the optimal design of development aid in the presence of network effects. More broadly, this research agenda helps bridge the gap between economics and sociology by formally modeling sociological concepts related to social capital and power in networks, and generates new mathematical results about probability in networks that contribute to computer science.