Algorithms pose interesting challenges to competition law, particularly discussing which practices involving this fast-paced technologies may or should be caught under Article 101 of the Treaty on the Functioning of the European Union ("TFEU"). As AI-driven pricing algorithms become increasingly...

Competition authorities impose substantial penalties on firms engaging in illegal pricefixing. We examine how basing cartel fines on either revenue, profit, or price overcharge influences cartel and market prices, as well as cartel incidence and stability. In an infinitely repeated Bertrand...

We study the propensity of independent algorithms to collude in repeated Cournot duopoly games. Specifically, we investigate the predictive power of different oligopoly and bargaining solutions regarding the effect of asymmetry between firms. We find that both consumers and firms can benefit...

We develop a method for detecting cartels in multistage auctions. Our approach allows a firm to be collusive when facing members of its cartel yet competitive when facing others. Intuitively, as initial bids are shaded, close initial bids not only imply similar costs but also provide an...

We develop a tractable model of competitive price cycles where prices are chosen alternatingly and consumers have heterogenous information. The model yields sharp empirical predictions about price patterns, impact of captive consumers and pass-through. Using rich station-level price data from...

Using a sample of listed Chinese firms from 2007 to 2020, we investigate the governance implications of cross-ownership in corporate bond markets. We find that cross-ownership significantly reduces bond issuance spreads, suggesting that synergistic governance effects outweigh potential collusion...