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Economic Allocations in Social Networks: Evidence and Theory

Final Report Summary - NETWORKS (Economic Allocations in Social Networks: Evidence and Theory)

Social networks affect many economic interactions, and the social capital embedded in them may help explain broad, macro level outcomes. In this project we combined evidence and theory to investigate the economic effects of networks and the underlying mechanisms. Here I group the main lessons from the project into three categories: (1) firm networks; (2) networks in development; (3) learning in networks.

Concerning firm networks, we used field experiments and observational data to establish two main results: that both larger firm networks and better peers in these networks substantially improve firm performance. To measure the effect of networks, in one key study we organized experimental business associations for firms in China. These associations lead to large and significant improvements in sales, profits and a range of other outcomes; and we documented learning from, and partnering with, peer firms as key mechanisms underlying these gains. We complemented this work with a study using observational data from Hungary, in which we showed that firm networks helped diffuse information about importing. These two studies establish the benefit of business networks. To measure the effect of peers within networks, we used data on supply chain networks from Hungary, and showed that inputs provided by foreign suppliers improved productivity substantially more than inputs provided by domestic suppliers. And we developed and implemented a methodology measuring the economic cost of allocating public procurement to politically connected suppliers, rather than to the efficient mix of suppliers. Taken together, these results highlight the economic and policy relevance of business connections, and help build a research agenda on firm networks.

In the context of networks in development, we showed how social networks both substitute for and complement formal credit markets. Using a model we showed that informal insurance constrained by the social network can achieve nearly full consumption smoothing, a result which helps explain basic facts about consumption insurance in development and highlights the potential of networks to substitute for formal markets. The insights from this analysis also informed my work exploring the effects of different constraint on consumption smoothing: consumption commitments. Building on the theory results, we empirically measured, using data from a field experiment in Peru, the high value of social ties for borrowing. This work has confirmed the importance of networks, but demonstrated that they can also complement markets because the collateral value of social links can increase repayment rates. Further evidence on the complementarity between networks and formal markets comes from our China studies, where we showed that communication in networks diffuses information about financing and thus enhances formal borrowing. Taken together, this work has expanded our understanding of the role of networks in shaping credit allocations, and may have helped seed the growing literature on network effects in development economics.

Concerning learning in networks, we both developed methodologies to empirically separate mechanisms and documented new mechanisms of learning. We combined data from a field experiment with a structural model to distinguish between different models of information aggregation in networks, and showed that limited transmission---when people do not pass on a particular piece of information---is both common and critical to account for in such an analysis. When doing so, we were able to reject an echo-chamber type bias in our experimental context. Building on this analysis, in our China study we explored the determinants of limited information transmission between firms, and found that product market competition was a key factor: firms were less willing to share business-relevant information with competitors. These results may open a new research direction on how the incentives to transmit information shape knowledge and beliefs.