Date: 2020
Type: Article
Artificial intelligence, algorithmic pricing, and collusion
American economic review, 2020, Vol. 110, No. 10, pp. 3267-3297
CALVANO, Emilio, CALZOLARI, Giacomo, DENICOLÒ, Vincenzo, PASTORELLO, Sergio, Artificial intelligence, algorithmic pricing, and collusion, American economic review, 2020, Vol. 110, No. 10, pp. 3267-3297
- https://hdl.handle.net/1814/70041
Retrieved from Cadmus, EUI Research Repository
Increasingly, algorithms are supplanting human decision-makers in pricing goods and services. To analyze the possible consequences, we study experimentally the behavior of algorithms powered by Artificial Intelligence (Q-learning) in a workhorse oligopoly model of repeated price competition. We find that the algorithms consistently learn to charge supracompetitive prices, without communicating with. one another. The high prices are sustained by collusive strategies with a finite phase of punishment followed by a gradual return to cooperation. This finding is robust to asymmetries in cost or demand, changes in the number of players, and various forms of uncertainty.
Additional information:
First published online: October 2020
Cadmus permanent link: https://hdl.handle.net/1814/70041
Full-text via DOI: 10.1257/aer.20190623
ISSN: 0002-8282; 1944-7981
Publisher: American Economic Association