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Cartel Dating

Author

Listed:
  • H. Peter Boswijk

    (University of Amsterdam, The Netherlands)

  • Maurice J.G. Bun

    (University of Amsterdam, The Netherlands)

  • Maarten Pieter Schinkel

    (University of Amsterdam, The Netherlands)

Abstract

The begin and end dates of cartels are often ambiguous, despite competition authorities stating them with precision. The legally established infringement period(s), based on documentary evidence, need not coincide with the period(s) of actual cartel effects. In this paper, we show that misdating cartel effects leads to a (weak) overestimation of but-for prices and an underestimation of overcharges. Total overcharges based on comparing but-for prices to actual prices are a (weak) underestimation of the true amount overcharged, irrespective of the type and size of the misdating. The bias in antitrust damage estimation based on predicted cartel prices can have either sign. We extend the before-during-and-after method with an empirical cartel dating procedure that uses multiple structural break tests to determine the actual begin and end date(s) of the effects of collusive agreements. Empirical findings in the European Sodium Chlorate cartel corroborate our theoretical results.

Suggested Citation

  • H. Peter Boswijk & Maurice J.G. Bun & Maarten Pieter Schinkel, 2016. "Cartel Dating," Tinbergen Institute Discussion Papers 16-092/VII, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20160092
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    1. Kai Hüschelrath & Kathrin Müller & Tobias Veith, 2013. "Concrete Shoes For Competition: The Effect Of The German Cement Cartel On Market Price," Journal of Competition Law and Economics, Oxford University Press, vol. 9(1), pages 97-123.
    2. Ulrich Laitenberger & Florian Smuda, 2015. "Estimating Consumer Damages In Cartel Cases," Journal of Competition Law and Economics, Oxford University Press, vol. 11(4), pages 955-973.
    3. Donald W. K. Andrews, 2003. "Tests for Parameter Instability and Structural Change with Unknown Change Point: A Corrigendum," Econometrica, Econometric Society, vol. 71(1), pages 395-397, January.
    4. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    5. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    6. Diebold, Francis X. & Chen, Celia, 1996. "Testing structural stability with endogenous breakpoint A size comparison of analytic and bootstrap procedures," Journal of Econometrics, Elsevier, vol. 70(1), pages 221-241, January.
    7. Marhsall, Robert C. & Marx, Leslie M., 2014. "The Economics of Collusion: Cartels and Bidding Rings," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262525941, December.
    8. Carsten J. Crede, 2015. "A structural break cartel screen for dating and detecting collusion," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2015-11, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    9. Perron, P, 1993. "Erratum [The Great Crash, the Oil Price Shock and the Unit Root Hypothesis]," Econometrica, Econometric Society, vol. 61(1), pages 248-249, January.
    10. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    11. Lawrence White, 2001. "Lysine and Price Fixing: How Long? How Severe?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 18(1), pages 23-31, February.
    12. James F. Nieberding, 2006. "Estimating overcharges in antitrust cases using a reduced-form approach: Methods and issues," Journal of Applied Economics, Universidad del CEMA, vol. 9, pages 361-380, November.
    13. Corbae,Dean & Durlauf,Steven N. & Hansen,Bruce E. (ed.), 2006. "Econometric Theory and Practice," Cambridge Books, Cambridge University Press, number 9780521807234, Enero-Abr.
    14. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    15. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    16. James F. Nieberding, 2006. "Estimating Overcharges in Antitrust Cases Using a Reduced-Form Approach: Methods and Issues," Journal of Applied Economics, Taylor & Francis Journals, vol. 9(2), pages 361-380, November.
    17. Marshall, Robert C. & Marx, Leslie M. & Raiff, Matthew E., 2008. "Cartel price announcements: The vitamins industry," International Journal of Industrial Organization, Elsevier, vol. 26(3), pages 762-802, May.
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    Cited by:

    1. Hellwig, Michael & Hüschelrath, Kai, 2018. "When Do Firms Leave Cartels? Determinants And The Impact On Cartel Survival," International Review of Law and Economics, Elsevier, vol. 54(C), pages 68-84.

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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices

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