Competition in Pricing Algorithms∗ Zach Y. Brown Alexander MacKay University of Michigany Harvard Universityz November 1, 2019 Abstract Increasingly, retailers have access to better pricing technology, especially in online mar- kets. Through pricing algorithms, firms can automate their response to rivals’ prices. What are the implications for price competition? We develop a model in which firms choose algo- rithms, rather than prices. Even with simple (i.e., linear) algorithms, competitive equilibria can have higher prices than in the standard simultaneous Bertrand pricing game. Using hourly prices of over-the-counter drugs from five major online retailers, we document evi- dence that these retailers possess different pricing technologies. In addition, we find pric- ing patterns consistent with competition in pricing algorithms. A simple calibration of the model suggests that pricing algorithms lead to meaningful increases in markups, especially for firms with superior pricing technology. ∗We thank Matt Grennan and Scott Kominers for helpful comments. We also thank seminar and conference participants at Harvard Business School and the IIOC. We are grateful for the research assistance of Alex Wu and Pratyush Tiwari. yUniversity of Michigan, Department of Economics. Email:
[email protected]. zHarvard University, Harvard Business School. Email:
[email protected]. 1 Introduction Increasingly, retailers have access to better pricing technology, especially in online markets. In particular, pricing algorithms allow retailers to commit to pricing strategies that depend on the prices of competitors. In this paper, we investigate how the presence of pricing algorithms affects equilibrium outcomes. We introduce a game in which firms choose algorithms, rather than prices, and we show that competitive equilibria of this game tend to have higher prices than the competitive price-setting equilibrium.