On the Optimal Design of Leniency Programmes

Agisilaou, Panayiotis (2013) On the Optimal Design of Leniency Programmes. Doctoral thesis, University of East Anglia.

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Abstract

Abstract
This thesis comprises of a collection of essays that aim at enhancing our under-
standing of the underlying mechanics of leniency policies in antitrust.
In Chapter 1, we provide a systematic overview of the most in�uential contribu-
tions to the literature on collusion and leniency policies, with a focus on antitrust
law. The survey elucidates the e¤ects of leniency programmes on cartel formation
and cartel implementation.
In Chapter 2, we provide a model to investigate the impact of a leniency pro-
gramme on collusive �rms�incentives to keep or destroy hard incriminating evi-
dence. We show that �rms may willfully keep the hard evidence to facilitate the
implementation of the cartel. Firms are more inclined to keep the hard evidence
when a leniency programme is available. Finally, �rms are more likely to destroy
the hard evidence when the collusive pro�ts-�ne ratio increases.
In Chapter 3, we study the strategic interaction between a cartel and an an-
titrust authority whose evidence against the cartel is private information. Within
the framework of a signalling game, we explore the antitrust authority�s incentives
to reveal the strength of its evidence, before committing to its prosecutorial e¤ort.
We show that, despite its potentially feeble evidence, the antitrust authority
can exploit its informational lead and induce the cartel to self-report at an earlier
stage of the prosecutorial process. The more generous the leniency programme,
the easier it is to induce self-reporting by the cartel.
In Chapter 4, we provide a model to characterize the optimal leniency pro-
gramme when colluding �rms can invest resources to avoid detection. We show
that the optimal �ne discount rate depends positively on the severity of the �ne
and negatively on the probability of investigation and the cost of avoidance ac-
tivities. A leniency programme that ignores �rms�e¤orts to avoid detection may
result in under-deterrence.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Social Sciences > School of Economics
Depositing User: Mia Reeves
Date Deposited: 05 Mar 2014 13:06
Last Modified: 05 Mar 2014 13:06
URI: https://ueaeprints.uea.ac.uk/id/eprint/47933
DOI:

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