In this note we analyze the sustainability of collusion in a game of repeated interaction where firms can price discriminate among consumers based on two types of customer data. This work is related to Liu and Serfes (2007) and Sapi and Suleymanova (2013). Following Sapi and Suleymanova we...

We analyze the effects of better algorithmic demand forecasting on collusive profits. We show that the comparative statics crucially depend on the whether actions are observable. Thus, the optimal antitrust policy needs to take into account the institutional settings of the industry in question....

We investigate the effects of passive backward acquisitions in their efficient upstream supplier on downstream firms' ability to collude in a dynamic game of price competition with homogeneous goods. We find that passive backward acquisitions impede downstream collusion. The main driver of our...

We analyze firms' ability to sustain collusion in a setting in which horizontally differentiated firms can price-discriminate based on private information regarding consumers' preferences. In particular, firms receive private signals which can be noisy (e.g., big data predictions). We find that...

Many cartels are formed by individual managers of different firms, but not by firms as collectives. However, most of the literature in industrial economics neglects individuals' incentives to form cartels. Although oligopoly experiments reveal important insights on individuals acting as firms,...

This paper investigates the collusive and competitive effects of algorithmic price recommendations on market outcomes. These recommendations are often non-binding and common in many markets, especially on online platforms. We develop a theoretical framework and derive two algorithms that...

The hypothesis that vertically integrated firms have an incentive to foreclose the input market because foreclosure raises its downstream rivals' costs is the subject of much controversy in the theoretical industrial organization literature. A powerful argument against this hypothesis is that,...

As self-learning pricing algorithms become popular, there are growing concerns among academics and regulators that algorithms could learn to collude tacitly on non-competitive prices and thereby harm competition. I study popular reinforcement learning algorithms and show that they develop...

Consumer switching costs cause the market demand of consumers who already bought a supplier's product to be less elastic while they simultaneously increase competition for new consumers. I study the effect of this twofold pricing incentive on firms' price setting behavior in a 2x2 factorial...

We analyze the pricing behavior of firms when explicit partial cartels have formed in experimental markets through communication. Using a repeated, asymmetric capacity constraint price game, we show that, in line with theory, a partial cartel is sufficient to increase market prices for all...