Competition in Pricing Algorithms

59 Pages Posted: 22 Nov 2019 Last revised: 29 Apr 2021

See all articles by Zach Brown

Zach Brown

University of Michigan

Alexander MacKay

Harvard University - Business School (HBS)

Multiple version iconThere are 2 versions of this paper

Date Written: April 29, 2021


Increasingly, retailers have access to better pricing technology, especially in online markets. Using hourly data from five major online retailers, we show that retailers set prices at regular intervals that differ across firms. In addition, faster firms appear to use automated pricing rules that are functions of rivals' prices. These features are inconsistent with the standard assumptions about pricing technology used in the empirical literature. Motivated by these facts, we consider a model of competition in which firms can differ in pricing frequency and choose pricing algorithms rather than prices. We demonstrate that, relative to the standard simultaneous price-setting model, pricing technology with these features can increase prices in Markov perfect equilibrium. A simple counterfactual simulation implies that pricing algorithms lead to meaningful increases in markups in our empirical setting, especially for firms with the fastest pricing technology.

Keywords: Pricing Algorithms, Pricing Frequency, Online Competition

JEL Classification: L40, D43, L81, L13, L86

Suggested Citation

Brown, Zach and MacKay, Alexander, Competition in Pricing Algorithms (April 29, 2021). Available at SSRN: or

Zach Brown

University of Michigan ( email )

611 Tappan Street
Ann Arbor, MI 48109-1220
United States

Alexander MacKay (Contact Author)

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Boston, MA 02163
United States


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