There is a growing market for pricing algorithms supplied by data analytics companies such as RealPage, a2i Systems, and Aprix. A data analytics company is likely to offer a better pricing algorithm than would be created internally by a firm because it has more expertise and experience, access to more data, and stronger incentives to invest in their development. At the same time, concerns have rightly been expressed by competition agencies – such as the UK's CMA and the German Monopolies Commission - that there could be anticompetitive effect when competitors adopt a pricing algorithm from the same third party. According to plaintiffs in multiple class action suits in the U.S., such concerns have been realised in the markets for apartment rentals and hotel rooms. In addition, recent studies find evidence of anticompetitive effect in the U.S. market for apartment rentals and the German retail gasoline market. In response to these concerns, the U.S. Senate has proposed legislation to constrain data analytics companies in how they use data and similar restrictions have been proposed and even implemented in several U.S. cities. This project explores the properties of a pricing algorithm when it is designed by a third party. Some of the questions addressed are:
If a third party’s objective is to maximise its profit from licensing the pricing algorithm to competitors, will it program in a supracompetitive markup? If a third party and competitors are part of a collusive agreement, as claimed in private litigation, what does this imply for how the pricing algorithm is designed?