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Analysis of current penalty schemes for violations of antitrust laws

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  • Motchenkova, E.

    (Tilburg University, School of Economics and Management)

  • Kort, P.M.

    (Tilburg University, School of Economics and Management)

Abstract

The main feature of the penalty schemes described in current sentencing guidelines is that the fine is based on the accumulated gains from cartel activities or price-fixing activities for the firm. The regulations suggest modeling the penalty as an increasing function of the accumulated illegal gains from price fixing to the firm, so that the history of the violation is taken into account. We incorporate these features of the penalty scheme into an optimal control model of a profit-maximizing firm under antitrust enforcement. To determine the effect of taking into account the history of the violation, we compare the outcome of this model with a model where the penalty is fixed. The analysis of the latter model implies that complete deterrence can be achieved only at the cost of shutting down the firm. The proportional scheme improves upon the fixed penalty, since it can ensure complete deterrence in the long run, even when penalties are moderate. Phase-diagram analysis shows that, the higher the probability and severity of punishment, the sooner cartel formation is blocked. Further, a sensitivity analysis is provided to show which strategies are most successful in reducing the degree of price fixing. It turns out that, when the penalties are already high, the antitrust policy aiming at a further increase in the severity of punishment is less efficient than the policy that increases the probability of punishment.
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Suggested Citation

  • Motchenkova, E. & Kort, P.M., 2006. "Analysis of current penalty schemes for violations of antitrust laws," Other publications TiSEM 0cbc7914-8fbb-40f5-8feb-c, Tilburg University, School of Economics and Management.
  • Handle: RePEc:tiu:tiutis:0cbc7914-8fbb-40f5-8feb-cd9ce3cbb28d
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    References listed on IDEAS

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    Cited by:

    1. Motchenkova, Evgenia, 2008. "Determination of optimal penalties for antitrust violations in a dynamic setting," European Journal of Operational Research, Elsevier, vol. 189(1), pages 269-291, August.
    2. Leliefeld, D. & Motchenkova, E., 2007. "To Protect in Order to Serve : Adverse Effects of Leniency Programs in View of Industry Asymmetry," Discussion Paper 2007-007, Tilburg University, Tilburg Law and Economic Center.
    3. Domenico De Giovanni & Fabio Lamantia, 2018. "Dynamic Harvesting Under Imperfect Catch Control," Journal of Optimization Theory and Applications, Springer, vol. 176(1), pages 252-267, January.
    4. Michael Makowsky, 2006. "An Agent-Based Model of Mortality Shocks, Intergenerational Effects, and Urban Crime," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(2), pages 1-7.
    5. Evgenia Motchenkova & Rob Laan, 2011. "Strictness of leniency programs and asymmetric punishment effect," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 58(4), pages 401-431, December.
    6. Maria Caterina Bramati & Arsen Palestini & Mauro Rota, 2016. "Effects of Law-Enforcement Efficiency and Duration of Trials in an Oligopolistic Competition Among Fair and Unfair Firms," Journal of Optimization Theory and Applications, Springer, vol. 170(2), pages 650-669, August.
    7. Evgenia MOTCHENKOVA & Daniel LELIEFELD, 2010. "Adverse Effects Of Corporate Leniency Programs In View Of Industry Asymmetry," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(2(12)/Sum), pages 114-128.
    8. Panayiotis Agisilaou, 2013. "Collusion in Industrial Economics and Optimally Designed Leniency Programmes - A Survey," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2013-03, Centre for Competition Policy, University of East Anglia, Norwich, UK..

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    More about this item

    JEL classification:

    • K21 - Law and Economics - - Regulation and Business Law - - - Antitrust Law
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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