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Publications
  • 2022
  • Article
  • Washington University Law Review

Dynamic Pricing Algorithms, Consumer Harm, and Regulatory Response

By: Alexander MacKay and Samuel N. Weinstein
  • Format:Electronic
  • | Pages:64
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Abstract

Pricing algorithms are rapidly transforming markets, from ride-sharing apps, to air travel, to online retail. Regulators and scholars have watched this development with a wary eye. Their focus so far has been on the potential for pricing algorithms to facilitate explicit and tacit collusion. This Article argues that the policy challenges pricing algorithms pose are far broader than collusive conduct. It demonstrates that algorithmic pricing can lead to higher prices for consumers in competitive markets and even in the absence of collusion. This consumer harm can be initiated by a single firm employing a superior pricing algorithm. Higher prices arise from the automated nature of algorithms, impacting any market where firms price algorithmically. Thus, pricing algorithms that are already in widespread use may allow sellers to extract a massive amount of wealth from consumers. Because this consumer harm arises even when firms do not collude, antitrust law cannot solve the problem. This Article looks to the history of pricing innovation in the early twentieth century to show how government can respond when new pricing technologies and strategies disrupt markets. It argues for pricing regulation as a feasible solution to the challenges non-collusive algorithmic pricing poses, and it proposes interventions targeted at when and how firms set prices.

Keywords

Competition Policy; Regulation; Algorithmic Pricing; Dynamic Pricing; Economics; Law And Economics; Law And Regulation; Consumer Protection; Antitrust Law; Industrial Organization; Antitrust Issues And Policies; Technological Change: Choices And Consequences; Competition; Policy; Price; Governing Rules, Regulations, and Reforms; Microeconomics; Duopoly and Oligopoly; Law

Citation

MacKay, Alexander, and Samuel N. Weinstein. "Dynamic Pricing Algorithms, Consumer Harm, and Regulatory Response." Washington University Law Review 100, no. 1 (2022): 111–174. (Direct download.)
  • SSRN
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More from the Authors
  • Estimating Models of Supply and Demand: Instruments and Covariance Restrictions By: Alexander MacKay and Nathan H. Miller
  • LIV Golf By: Alexander J. MacKay
  • Self-Preferencing at Amazon: Evidence from Search Rankings By: Chiara Farronato, Andrey Fradkin and Alexander MacKay
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