Self-reporting in optimal law enforcement with criminal teams, multiple stages, and ex post asymmetric information
This thesis analyzes self-reporting as a tool in optimal law enforcement. In particular, the contribution focuses on the option value created by a self-reporting scheme if violators receive private information about their detection or conviction probability extit{after} they have committed a crime (ex-post asymmetric information). This option value creates a drawback of amnesty programs that has not been taken into account in the literature. We derive optimal fine reductions for different crime characteristics (i.e. different degrees of ex-post heterogeneity) analyze the relationship between fine reductions for violators that have not yet been convicted and violators who start to cooperate with the authority already after a litigation started. The remainder of the thesis focuses on self-reporting as a useful enforcement tool against criminal teams. If members of such teams act non-cooperatively in the self-reporting stage, we show that they can be driven into Prisoner's Dilemma situations such that aggregated team fines increase due to a reduction of fines for single self-reporters. Finally, we apply our theoretical findings to a detailed comparison of the corporate leniency programs recently enacted in the EU and the USA.
info:eu-repo/classification/ddc/330, Selbstanzeige, Asymmetrische Information, Ökonomische Theorie des Rechts, Wirtschaft, Law and Economics, Cartel Prosecution
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