Collaborative Research: Information, Markets and Networks

Yale University, New Haven CT

Investigators

Abstract

Classical market analysis built in the assumption that market participants interact in a single market with the same information. Research over the last forty years has highlighted the importance of asymmetric information in markets. Research over the last twenty years has highlighted the importance of limited participation in markets via network linkages. The project develops new approaches to studying the role of information and networks in markets. The classical approach to analyzing asymmetric information in economic settings is to understand the consequences of assuming one particular information structure. In this paper, we develop an alternative approach to understanding what can happen in all information structures. This alternative approach delivers powerful tools and new insights about the role of information in markets. The project builds on earlier work supported by the NSF on what can happen in strategic situations across different information structures. The first component of the project on "Information and Markets" applies that approach to classical market settings. In this context, the approach highlights the distinct roles of information in making more outcomes feasible but also in imposing more incentive constraints on what can happen. The approach also clarifies the strategic foundations of competitive equilibria under asymmetric information. A second component on "Information and Price Discrimination" looks at outcomes under price discrimination, generalizing prior work on single good monopoly. A third component of the project is on "Information, Networks and Volatility". The problems of arbitrary networks and arbitrary information structures are tightly linked. Building on earlier work for symmetric environments and interaction, we examine which information structure generates the most volatility in an economy with both idiosyncratic and aggregate shocks in arbitrary networks with general information structures.