Learning to Collude Tacitly on Production Levels by Oligopolistic Agents

Abstract Classical oligopoly theory has strong analytical foundations but is weak in capturing the operating environment of oligopolists and the available knowledge they have for making decisions, areas in which the management literature is relevant. We use agent-based models to simulate the impact on firm profitability of policies that oligopolists can pursue when setting production levels. We develop an approach to analyzing simulation results that makes use of nonparametric statistical tests, taking advantage of the large amounts of data generated by simulations, and avoiding the assumption of normality that does not necessarily hold. Our results show that in a quantity game, a simple exploration rule, which we call Probe and Adjust, can find either the Cournot equilibrium or the monopoly solution depending on the measure of success chosen by the firms. These results shed light on how tacit collusion can develop within an oligopoly