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.

Grantor dc:publisher

Publikationsserver der RWTH Aachen University

Year dc:date

2003

Author dc:creator

• Walzl, Markus

Contributors dc:contributor

• Feess, Eberhard

• info:eu-repo/classification/ddc/330
• Selbstanzeige
• Asymmetrische Information
• Ökonomische Theorie des Rechts
• Wirtschaft
• Law and Economics
• Cartel Prosecution

Statement dc:rights

• info:eu-repo/semantics/openAccess

Language dc:language

eng

Identifier

https://publications.rwth-aachen.de/search?p=id:%22RWTH-CONV-123599%22

OAI identifier oai:identifier

oai:publications.rwth-aachen.de:61998