Networks, Frictions, and Price Dispersion

This paper models frictions in buyer-seller markets using networks, where buyers are linked with a subset of sellers and sellers are linked with a subset of buyers. Sparser networks are associated with higher search frictions. We use the model to characterize pairwise stable allocations and their supporting prices. Our approach allows for network effects, where a buyer who is not linked to a seller affects the price obtained by that seller. Network effects generate the central finding of our paper: even relatively sparse networks lead to price distributions and allocations that are close to the perfectly competitive outcome where the law of one price holds. We then investigate the role of network effects in a dynamic setting by studying wages in the context of an on-the-job search model. We find two novel predictions relative to the search literature. Lowering frictions (so that workers receive job offers at a higher rate) leads to: (1) lower worker mobility and lower expected wage growth and (2) lower expected wages in markets with high unemployment. We argue that our framework is suited to the analysis of a wide range of real-world markets, such as the labor market and buyer-seller trading platforms like eBay or Amazon.