Legal opinion is divided on whether predicable sentences are a good thing for the administration of justice. In the case of cartel violations, both the United States and the EU have introduced guidelines for calculating fines that are intended to make fining decisions more transparent and to...

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...

For criminal violations of the Sherman Act, although guided by federal sentencing guidelines, U.S. Department of Justice has great latitude in recommending corporate cartel fines to the federal courts, and its recommendations are nearly always determinative. In this paper, we analyze the...

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 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....

This paper discusses the question whether self-learning price-setting algorithms are able to coordinate their pricing behaviour to achieve a collusive outcome that maximizes the joint profits of the firms using these algorithms. While the legal literature generally assumes that algorithmic...

The key role played by public information in market economies is paramount. Yet, investigation on how prices are affected is hindered by intricate endogeneity and parametrization issues. This paper contributes to the literature by identifying and studying a case where public information is...