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Analysis of Current Penalty Schemes for Violations of Antitrust Laws

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  • Kort, P. M.
  • Motchenkova, E.

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.

Suggested Citation

  • Kort, P. M. & Motchenkova, E., 2006. "Analysis of Current Penalty Schemes for Violations of Antitrust Laws," MPRA Paper 17227, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:17227
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    References listed on IDEAS

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    1. Garoupa, Nuno, 2001. "Optimal magnitude and probability of fines," European Economic Review, Elsevier, vol. 45(9), pages 1765-1771, October.
    2. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters,in: Essays in the Economics of Crime and Punishment, pages 1-54 National Bureau of Economic Research, Inc.
    3. Emons, Winand, 2003. "A note on the optimal punishment for repeat offenders," International Review of Law and Economics, Elsevier, vol. 23(3), pages 253-259, September.
    4. Gustav Feichtinger, 1983. "A Differential Games Solution to a Model of Competition Between a Thief and the Police," Management Science, INFORMS, vol. 29(6), pages 686-699, June.
    5. Leung, Siu Fai, 1991. "How to make the fine fit the corporate crime? : An analysis of static and dynamic optimal punishment theories," Journal of Public Economics, Elsevier, vol. 45(2), pages 243-256, July.
    6. Garoupa, Nuno, 1997. " The Theory of Optimal Law Enforcement," Journal of Economic Surveys, Wiley Blackwell, vol. 11(3), pages 267-295, September.
    7. Polinsky, Mitchell & Shavell, Steven, 1979. "The Optimal Tradeoff between the Probability and Magnitude of Fines," American Economic Review, American Economic Association, vol. 69(5), pages 880-891, December.
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    Cited by:

    1. repec:spr:joptap:v:170:y:2016:i:2:d:10.1007_s10957-016-0866-5 is not listed on IDEAS
    2. 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.

    More about this item

    Keywords

    Optimal Control; Dynamic Analysis; Antitrust Policy; Antitrust Laws;

    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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