We dedicate this paper to the memory of Toni Calvó-Armengol. As will be clear in the subsequent pages, he has made a lasting contribution to our thinking about networks and economics. We deeply miss his insight and his company. We are grateful to Alexander Groves for research assistance and to Noga Alon, Roland Bénabou, Francis Bloch, Andrea Galeotti, Sanjeev Goyal, Matthew Jackson, Antoine Loeper, Brian Rogers, and Yves Zenou and participants in seminars and conferences at Barcelona, Berkeley, Caltech, Cambridge, Duke, École Polytechnique
Abstract:This paper brings a general network analysis to a wide class of economic games. A network, or interaction matrix, tells who directly interacts with whom. A major challenge is determining how network structure shapes overall outcomes. We have a striking result. Equilibrium conditions depend on a single number: the lowest eigenvalue of a network matrix. Combining tools from potential games, optimization, and spectral graph theory, we study games with linear best replies and characterize the Nash and stable equilibria for any graph and for any impact of players' actions. When the graph is sufficiently absorptive (as measured by this eigenvalue), there is a unique equilibrium. When it is less absorptive, stable equilibria always involve extreme play where some agents take no actions at all. This paper is the first to show the importance of this measure to social and economic outcomes, and we relate it to different network link patterns.