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Simulation and Prosecution of a Cartel with Endogenous Cartel Formation

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  • Johannes Paha

    () (Justus-Liebig-University Gießen)

Abstract

In many cases, collusive agreements are formed by asymmetric firms and include only a subset of the firms active in the cartelized industry. This paper endogenizes the process of cartel formation in a numeric simulation model where firms differ in marginal costs and production technologies. The paper models the incentive to collude in a differentiated products Bertrand-oligopoly. Cartels are the outcomes of a dynamic formation game in mixed strategies. I find that the Nash-equilibrium of this complex game can be obtained efficiently by a Differential Evolution stochastic optimization algorithm. It turns out that large firms have a higher probability to collude than small firms. Since firms' characteristics evolve over time, the simulation is used to generate data of costs, prices, output-quantities, and profits. This data forms the basis for an evaluation of empirical methods used in the detection of cartels.

Suggested Citation

  • Johannes Paha, 2010. "Simulation and Prosecution of a Cartel with Endogenous Cartel Formation," MAGKS Papers on Economics 201007, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  • Handle: RePEc:mar:magkse:201007
    as

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    File URL: http://www.uni-marburg.de/fb02/makro/forschung/magkspapers/07-2010_paha.pdf
    File Function: First version, 2010
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    References listed on IDEAS

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    5. Mattheos Protopapas & Francesco Battaglia & Elias Kosmatopoulo, 2008. "Coevolutionary Genetic Algorithms for Establishing Nash Equilibrium in Symmetric Cournot Games," Working Papers 004, COMISEF.
    6. Stephen Davies & Matthew Olczak, 2008. "Tacit versus Overt Collusion Firm Asymmetries and Numbers: What’s the Evidence?," Working Papers 08-32, Centre for Competition Policy, University of East Anglia.
    7. Jenny X. Li & Peter Winker, 2003. "Time Series Simulation with Quasi Monte Carlo Methods," Computational Economics, Springer;Society for Computational Economics, vol. 21(1_2), pages 23-43, February.
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    9. Johannes Paha, 2011. "Empirical methods in the analysis of collusion," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 38(3), pages 389-415, July.
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    More about this item

    Keywords

    Collusion; Cartel Detection; Cartel Formation; Differential Evolution; Heuristic Optimization; Industry Simulation;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L12 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Monopoly; Monopolization Strategies
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L40 - Industrial Organization - - Antitrust Issues and Policies - - - General

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