Antitrust & Competition Policy Blog

Editor: D. Daniel Sokol
University of Florida
Levin College of Law

Tuesday, February 19, 2019

Artificial Intelligence, Algorithmic Pricing and Collusion

Emilio Calvano, University of Bologna - Department of Economics; University of Toulouse 1 - Department of Economics; CSEF - Center for Studies in Economics and Finance, Giacomo Calzolari, European University Institute - Economics Department (ECO); Centre for Economic Policy Research (CEPR); University of Bologna, Vincenzo Denicolò, University of Bologna, and Sergio Pastorello, University of Bologna - Department of Economics have a fascinating paper on Artificial Intelligence, Algorithmic Pricing and Collusion. Worth downloading!

ABSTRACT: Pricing algorithms are increasingly replacing human decision making in real marketplaces. To inform the competition policy debate on possible consequences, we run experiments with pricing algorithms powered by Artificial Intelligence in controlled environments (computer simulations).
In particular, we study the interaction among a number of Q-learning algorithms in the context of a workhorse oligopoly model of price competition with Logit demand and constant marginal costs. We show that the algorithms consistently learn to charge supra-competitive prices, without communicating with each other. The high prices are sustained by classical collusive strategies with a finite punishment phase followed by a gradual return to cooperation. This finding is robust to asymmetries in cost or demand and to changes in the number of players.

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