We analyze how leniency affects cartel pricing in an infinitely-repeated oligopoly model where the fine rates are linked to illegal gains and detection probabilities depend on the degree of collusion. A novel aspect of this study is that we focus on the worst possible outcome. We investigate the...

We analyze maximal cartel prices in infinitely-repeated oligopoly models under leniency where fines are linked to illegal gains, as often outlined in existing antitrust regulation, and detection probabilities depend on the degree of collusion. We introduce cartel culture that describes how...

As a part of their industry or competition policies governments decide whether to allow for free market entry of firms or to regulate market access. We analyze a model where governments (ab)use these policy decisions for strategic reasons in an international setting. Multiple equilibria of this...

The paper aims at assessing the costs and benefits of antitrust enforcement. The analysis starts with an investigation of why competition is typically worth protecting followed by a collection of empirical evidence which shows that competition actually needs protection by antitrust policy in...

This essay links some of my own work on expectations, learning and bounded rationality to the inspiring ideas of Jean-Michel Grandmont. In particular, my work on consistent expectations and behavioral learning equilibria may be seen as formalizations of JMG's ideas of self-fulfilling mistakes....

We discuss recent work on bounded rationality and learning in relation to Soros' principle of reflexivity and stress the empirical importance of non-rational, almost self-fulfilling equilibria in positive feedback systems. As an empirical example, we discuss a behavioral asset pricing model with...