I study the predictability of the EC’s merger decision procedure before and after the 2004 merger policy reform based on a dataset covering all affected markets of mergers with an official decision documented by DG Comp between 1990 and 2014. Using the highly flexible, non-parametric random...

Lacking predictability of competition-law enforcement has its costs. This paper shows that academic analyses of what competition laws should look like do not always treat this factor adequately, paying instead excessive attention to the problem of error. Namely, some analyses completely ignore...

I study the predictability of the EC's merger decision procedure before and after the 2004 merger policy reform based on a dataset covering all affected markets of mergers with an official decision documented by DG Comp between 1990 and 2014. Using the highly flexible, non-parametric random...

I study the predictability of the EC’s merger decision procedure before and after the 2004 merger policy reform based on a dataset covering all affected markets of mergers with an official decision documented by DG Comp between 1990 and 2014. Using the highly flexible, non-parametric random...

Scholars and enforcement officials debate the merits and implications of “behavioral antitrust” — the application of empirical evidence showing how human behavior departs systematically and predictably from strict rationality (“bounded rationality”) to antitrust law. Notwithstanding...

This article distills insights about cartel formation from 41 cases prosecuted by the European Commission between 2001 and 2010. The case studies examine the events occurring in the industries prior to the cartels' set-up and identify the following potential causes for cartel formation: Changes...

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 build a game-theoretic model to examine how better demand forecasting due to algorithms, machine learning and artificial intelligence affects the sustainability of collusion in an industry. We find that while better forecasting allows colluding firms to better tailor prices to demand...

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....