Affiliation:
1. Department of Economics, University of Michigan and NBER (email: )
2. Harvard Business School (email: )
Abstract
We document new facts about pricing technology using high-frequency data, and we examine the implications for competition. Some online retailers employ technology that allows for more frequent price changes and automated responses to price changes by rivals. Motivated by these facts, we consider a model in which firms can differ in pricing frequency and choose pricing algorithms that are a function of rivals’ prices. In competitive (Markov perfect) equilibrium, the introduction of simple pricing algorithms can increase price levels, generate price dispersion, and exacerbate the price effects of mergers. (JEL D21, D22, D43, G34, L13, L81)
Publisher
American Economic Association
Subject
General Economics, Econometrics and Finance
Reference57 articles.
1. Asker, John, Chaim Fershtman, and Ariel Pakes. 2022. "The Impact of AI Design on Pricing." Unpublished.
2. Assad, Stephanie, Robert Clark, Daniel Ershov, and Lei Xu. 2022. "Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market." Unpublished.
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