Hub-and-Spoke Collusion with a Third-Party Pricing Algorithm

Hub-and-Spoke Collusion with a Third-Party Pricing Algorithm

Joseph E. Harrington Jr

University of Pennsylvania

Abstract

A new form of hub-and-spoke collusion has purportedly emerged: A data analytics company (hub) coordinates the prices of competitors (spokes) through the pricing algorithm that it supplies to them. The presence of such a hub-and-spoke cartel has been claimed in private litigation in the markets for apartments and hotel rooms. This paper explores hub-and-spoke collusion in this setting. The novel feature is that a data analytics company delivers an efficiency as its pricing algorithm is more effective in having price respond to demand variation. Stable collusion is shown to be feasible even when there are many small firms. Furthermore, the magnitude of the supracompetitive markup is increasing in the efficiency delivered by the third party. To my knowledge, this is the first theory to show how an efficiency can be a driver of collusion. This relationship poses a challenge when it comes to designing an effective remedy, for it is exactly those markets with the greatest procompetitive efficiencies that have the greatest risk of anticompetitive harm.