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Determination of Optimal Penalities for Antitrust Violations in a Dynamic Setting

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  • Motchenkova, E.

    (Tilburg University, TILEC)

Abstract

We analyze a differential game describing the interactions between a firm that might be violating competition law and the antitrust authority.The objective of the authority is to minimize social costs (loss in consumer surplus) induced by an increase in prices above marginal costs.It turns out that the penalty schemes which are used now in EU and US legislation appear not to be as efficient as desired from the point of view of minimization of consumer loss from price-fixing activities of the .rm.In particular, we prove that full compliance behavior is not sustainable as a Nash Equilibrium in Markovian strategies over the whole planning period, and, moreover, that it will never arise as the long-run steadystate equilibrium of the model.We also investigate the question which penalty system enables us to completely deter cartel formation in a dynamic setting.We found that this socially desirable outcome can be achieved in case the penalty is an increasing function of the degree of offence and is negatively related to the probability of law enforcement.
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Suggested Citation

  • Motchenkova, E., 2004. "Determination of Optimal Penalities for Antitrust Violations in a Dynamic Setting," Discussion Paper 2004-019, Tilburg University, Tilburg Law and Economic Center.
    • Handle: RePEc:tiu:tiutil:ebc993e1-9181-41e0-8d5c-d8993da06433
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    Cited by:

    1. Beata Grzyl & Magdalena Apollo & Adam Kristowski, 2019. "Application of Game Theory to Conflict Management in a Construction Contract," Sustainability, MDPI, vol. 11(7), pages 1-12, April.
    2. Martin Schmidt, 2014. "Fines for Administrative Offences in Public Procurement: An Econometric Model [Pokuty za správní delikty ve veřejných zakázkách: ekonometrický model]," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2014(6), pages 35-50.
    3. 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.
    4. Shitao Gong & Xin Gao & Zhou Li & Linyan Chen, 2021. "Developing a Dynamic Supervision Mechanism to Improve Construction Safety Investment Supervision Efficiency in China: Theoretical Simulation of Evolutionary Game Process," IJERPH, MDPI, vol. 18(7), pages 1-29, March.
    5. Plaček Michal & Ochrana František & Schmidt Martin & Půček Milan, 2016. "The Evaluation of the Role of the Office for Protection of Competition of the Czech Republic in Regulating Public Procurement," NISPAcee Journal of Public Administration and Policy, Sciendo, vol. 9(1), pages 97-116, June.
    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. Merino Troncoso, Carlos, 2019. "Optimal dynamic antitrust fines," MPRA Paper 96781, University Library of Munich, Germany.

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    More about this item

    JEL classification:

    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices
    • K21 - Law and Economics - - Regulation and Business Law - - - Antitrust Law
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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