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Beschreibung:
To explore the efficacy of a corporate leniency program, a Markov process is constructed which models the stochastic formation and demise of cartels. Cartels are born when given the opportunity and market conditions are right, while cartels die because of internal collapse or they are caught and convicted by the antitrust authority. The likelihood that a cartel, once identified, is convicted depends inversely on the caseload of the antitrust authority due to an implicit resource constraint. The authority also chooses an enforcement policy in terms of the fraction of non-leniency cases that it prosecutes. Using numerical analysis, the impact of a leniency program on the steady-state cartel rate is investigated. Holding the enforcement policy of the antitrust authority fixed, a leniency program lowers the frequency of cartels. However, the additional caseload provided by the leniency program induces the antitrust authority to prosecute a smaller fraction of cartel cases identified outside of the program. Because of this less aggressive enforcement policy, it is possible that the cartel rate is higher when there is a leniency program.