International Conference on Economics, Finance & Business, Prague

LENIENCY POLICY AGAINST REPEAT OFFENDERS

DEJAN TRIFUNOVIC, BOJAN RISTIC, NIKOLA ILIĆ

Abstract:

Dominant reliance on leniency for detecting cartels in the EU resulted in generous fine reductions, where repeat offenders benefit more than other cartel members. This behavior of repeat offenders undermines the purpose of the leniency program. This paper considers the design of a leniency policy that aims to deter repeat offenders from entirely participating in cartels by using the game-theoretic approach. Repeat offenders should pay higher fines than first-time offenders. Comparative statics results reveal that this increase in fines for repeat offenders depends on several factors. A lower probability of investigation and lower fines for first-time offenders require higher upward adjustment of fines for repeat offenders. Higher cheating profit undermines the stability of collusion, and it is unnecessary to increase the fines for repeat offenders significantly. The model is calibrated based on the empirical estimates in the literature on the probability of cartel detection in the EU.

Keywords: collusion, leniency, fine reduction, repeat offenders.