Algorithmic collusion with imperfect monitoring
International journal of industrial organization, 2021, Vol. 79, Art. 102712, OnlineOnly
CALVANO, Emilio, CALZOLARI, Giacomo, DENICOLO, Vincenzo, PASTORELLO, Sergio, Algorithmic collusion with imperfect monitoring, International journal of industrial organization, 2021, Vol. 79, Art. 102712, OnlineOnly - https://hdl.handle.net/1814/73708
Retrieved from Cadmus, EUI Research Repository
We show that if they are allowed enough time to complete the learning, Q-learning algorithms can learn to collude in an environment with imperfect monitoring adapted from Green and Porter (1984), without having been instructed to do so, and without communicating with one another. Collusion is sustained by punishments that take the form of “price wars” triggered by the observation of low prices. The punishments have a finite duration, being harsher initially and then gradually fading away. Such punishments are triggered both by deviations and by adverse demand shocks.
Published online: 14 February 2021
Cadmus permanent link: https://hdl.handle.net/1814/73708
Full-text via DOI: 10.1016/j.ijindorg.2021.102712