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A Cointegration-based cartel screen for detecting collusion

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  • Kurdoglu, Berkay
  • Yucel, Eray

Abstract

In this article, we propose a new empirical screen for detecting cartels, using the cointegration as our basis of modeling. The proposed screen is capable of identifying potential cartel behavior, indicating the strength of price adjustment among firms, and providing a basis for assessing structural change. The screen is applied to the Turkish cement market for an initial demonstration of use; we obtain promising results.

Suggested Citation

  • Kurdoglu, Berkay & Yucel, Eray, 2022. "A Cointegration-based cartel screen for detecting collusion," MPRA Paper 113888, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:113888
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    File URL: https://mpra.ub.uni-muenchen.de/113888/1/MPRA_paper_113888.pdf
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    References listed on IDEAS

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    1. Bejger, Sylwester, 2012. "Cartel in the Indian cement industry: An attempt to identify it," Economics Discussion Papers 2012-18, Kiel Institute for the World Economy (IfW Kiel).
    2. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    3. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    4. Carsten J. Crede, 2019. "A Structural Break Cartel Screen for Dating and Detecting Collusion," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 54(3), pages 543-574, May.
    5. Abrantes-Metz, Rosa M. & Froeb, Luke M. & Geweke, John & Taylor, Christopher T., 2006. "A variance screen for collusion," International Journal of Industrial Organization, Elsevier, vol. 24(3), pages 467-486, May.
    6. Andreoli-Versbach, Patrick & Franck, Jens-Uwe, 2013. "Actions Speak Louder than Words: Econometric Evidence to Target Tacit Collusion in Oligopolistic Markets," Discussion Papers in Economics 16179, University of Munich, Department of Economics.
    7. Rosa Abrantes-Metz, 2014. "Recent Successes of Screens for Conspiracies and Manipulations: Why Are There Still Skeptics?â€," Antitrust Chronicle, Competition Policy International, vol. 10.
    8. Robert H. Porter & J. Douglas Zona, 1999. "Ohio School Milk Markets: An Analysis of Bidding," RAND Journal of Economics, The RAND Corporation, vol. 30(2), pages 263-288, Summer.
    9. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    10. José Manuel Ordóñez-de-Haro & José Luis Torres, 2014. "Price Hysteresis After Antitrust Enforcement: Evidence From Spanish Food Markets," Journal of Competition Law and Economics, Oxford University Press, vol. 10(1), pages 217-256.
    11. Alfred A. Haug, 2002. "Temporal Aggregation and the Power of Cointegration Tests: a Monte Carlo Study," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 399-412, September.
    12. Johannes Wachs & J'anos Kert'esz, 2019. "A network approach to cartel detection in public auction markets," Papers 1906.08667, arXiv.org.
    13. Patrick Bajari & Lixin Ye, 2003. "Deciding Between Competition and Collusion," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 971-989, November.
    14. Juan Jiménez & Jordi Perdiguero, 2012. "Does Rigidity of Prices Hide Collusion?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 41(3), pages 223-248, November.
    15. Silveira, Douglas & Vasconcelos, Silvinha & Resende, Marcelo & Cajueiro, Daniel O., 2022. "Won’t Get Fooled Again: A supervised machine learning approach for screening gasoline cartels," Energy Economics, Elsevier, vol. 105(C).
    16. Porter, Robert H & Zona, J Douglas, 1993. "Detection of Bid Rigging in Procurement Auctions," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 518-538, June.
    17. Hans W. Friederiszick & Frank P. Maier-Rigaud, 2008. "Triggering Inspections Ex Officio: Moving Beyond A Passive Eu Cartel Policy," Journal of Competition Law and Economics, Oxford University Press, vol. 4(1), pages 89-113.
    18. Engle, R. F. & Granger, C. W. J. (ed.), 1991. "Long-Run Economic Relationships: Readings in Cointegration," OUP Catalogue, Oxford University Press, number 9780198283393.
    19. Froeb, Luke M. & Koyak, Robert A. & Werden, Gregory J., 1993. "What is the effect of bid-rigging on prices?," Economics Letters, Elsevier, vol. 42(4), pages 419-423.
    20. Engle, R.F. & Yoo, B.S., 1989. "Cointegrated Economic Time Series: A Survey With New Results," Papers 8-89-13, Pennsylvania State - Department of Economics.
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    More about this item

    Keywords

    Antitrust; Cartel; Detection; Empirical screen;
    All these keywords.

    JEL classification:

    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices

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