Hansen, Karsten T.Misra, KanishkaPai, Mallesh M.2021-03-102021-03-102021Hansen, Karsten T., Misra, Kanishka and Pai, Mallesh M.. "Frontiers: Algorithmic Collusion: Supra-competitive Prices via Independent Algorithms." <i>Marketing Science,</i> 40, no. 1 (2021) INFORMS: https://doi.org/10.1287/mksc.2020.1276.https://hdl.handle.net/1911/110164Motivated by their increasing prevalence, we study outcomes when competing sellers use machine learning algorithms to run real-time dynamic price experiments. These algorithms are often misspecified, ignoring the effect of factors outside their control, for example, competitors’ prices. We show that the long-run prices depend on the informational value (or signal-to-noise ratio) of price experiments: if low, the long-run prices are consistent with the static Nash equilibrium of the corresponding full information setting. However, if high, the long-run prices are supra-competitive—the full information joint monopoly outcome is possible. We show that this occurs via a novel channel: competitors’ algorithms’ prices end up running correlated experiments. Therefore, sellers’ misspecified models overestimate the own price sensitivity, resulting in higher prices. We discuss the implications on competition policy.engThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by INFORMS.Journal articlehttps://doi.org/10.1287/mksc.2020.1276