Community Structure and Market Outcomes: A Repeated Games in Networks Approach

Consider a large market with asymmetric information, in which sellers choose whether to cooperate or deviate and ‘cheat’ their buyers, and buyers decide whether to re-purchase from different sellers. We model active trade relationships as links in a buyer-seller network and suggest a framework for studying repeated games in such networks. In our framework, buyers and sellers have rich yet incomplete knowledge of the network structure; allowing us to derive meaningful conditions that determine whether a network is consistent with trade and cooperation between every buyer and seller that are connected. We show that three network features reduce the minimal discount factor necessary for sustaining cooperation: moderate competition, sparseness, and segregation. We find that the incentive constraints rule out networks that maximize the volume of trade and that the constrained trade maximizing networks are in between ‘old world’ segregated and sparse networks, and a ‘global market’