I study a monopolistic pricing problem in which the consumer performs product research to determine whether or not to purchase a good. The consumer receives a signal of quality via a Brownian motion process with a type-dependent drift. I fully characterize the consumer's optimal strategy; she...

Increasingly, firms use algorithms powered by artificial intelligence to set prices. Previous research studies interactions among Q-learning algorithms in a simulated oligopoly model of price competition. The algorithms learn collusive strategies but require a long time that corresponds to...

We study third-degree price discrimination in the presence of uninformed buyers who extract noisy information from observing prices. In a noisy learning environment, price discrimination can be detrimental to the firm and beneficial to the consumers. On the one hand, discriminatory pricing...

We study optimal experimentation by a monopolistic platform in a two-sided market. The platform provider is uncertain about the strength of the externality each side is exerting on the other. Setting participation fees on both sides, it gradually learns about these externalities by observing...

We study dynamic market competition between a monopoly incumbent and an entrant experimenting with disruptive innovation. The monopolist can only pursue the uncertain innovation if it buys the disruptor, who is more efficient and privately knows its ability. Mergers generate synergies. We...

Consumers choosing flat-rate contracts tend to have insufficient usage to warrant the cost, particularly for new products. We propose and estimate a Bayesian learning model of tariff and usage choice that explains this "flat-rate bias'' without relying on behavioral misjudgments or...

We study how learning affects an uninformed monopolist's supply and investment decisions under multiplicative uncertainty in demand. The monopolist is uninformed because it does not know one of the parameters defining the distribution of the random demand. Observing prices reveals this...

The widespread use of market-making algorithms in electronic over-the-counter markets may give rise to unexpected effects resulting from the autonomous learning dynamics of these algorithms. In particular the possibility of `tacit collusion' among market makers has increasingly received...

We develop a nonlinear duopoly model in which the heuristic expectation formation and learning behavior of two boundedly rational firms may engender complex dynamics. Most importantly, we assume that the firms employ different forecasting models to predict the behavior of their opponent....

We address the issue of risk aversion in a competitive equilibrium when some buyers engage in learning and information is conveyed through the price system. Specifically, since the learning process yields uncertainty, we study the effect of risk aversion on the equilibrium outcomes of the model,...