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A structural break cartel screen for dating and detecting collusion

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  • Carsten J. Crede

    (Centre for Competition Policy and School of Economics, University of East Anglia)

Abstract

In this paper, a new empirical screen for detecting cartels is developed. It can also be used to date the beginning of known conspiracies, which is often difficult in practice. Structural breaks that are induced by cartels in the data generating process (DGP) of industry prices are detected by testing reduced form price equations for structural instability. The new screen is applied to three European markets for pasta products, and it successfully reports the cartels that were present in the Italian and Spanish markets, but finds no suspicious patterns in the French market, which was not cartelised.

Suggested Citation

  • 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..
    • Handle: RePEc:uea:ueaccp:2015_11
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    References listed on IDEAS

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    1. John Connor, 2005. "Collusion and price dispersion," Applied Economics Letters, Taylor & Francis Journals, vol. 12(6), pages 335-338.
    2. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2002. "strucchange: An R Package for Testing for Structural Change in Linear Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i02).
    3. Kai Hüschelrath & Tobias Veith, 2014. "Cartel Detection in Procurement Markets," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 35(6), pages 404-422, September.
    4. Baker, Jonathan B & Rubinfeld, Daniel L, 1999. "Empirical Methods in Antitrust Litigation: Review and Critique," American Law and Economics Review, Oxford University Press, vol. 1(1-2), pages 386-435, Fall.
    5. Zeileis, Achim & Kleiber, Christian & Kramer, Walter & Hornik, Kurt, 2003. "Testing and dating of structural changes in practice," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 109-123, October.
    6. Pim Heijnen & Marco A. Haan & Adriaan R. Soetevent, 2015. "Screening for collusion: a spatial statistics approach," Journal of Economic Geography, Oxford University Press, vol. 15(2), pages 417-448.
    7. 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.
    8. 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.
    9. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    10. Giovanni Notaro, 2014. "Methods For Quantifying Antitrust Damages: The Pasta Cartel In Italy," Journal of Competition Law and Economics, Oxford University Press, vol. 10(1), pages 87-106.
    11. Blanckenburg Korbinian von & Kholodilin Konstantin A. & Geist Alexander, 2012. "The Influence of Collusion on Price Changes: New Evidence from Major Cartel Cases," German Economic Review, De Gruyter, vol. 13(3), pages 245-256, August.
    12. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    13. Rosa Abrantes-Metz & Patrick Bajari, 2010. "Screens for Conspiracies and Their Multiple Applications," CPI Journal, Competition Policy International, vol. 6.
    14. 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.
    15. 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.
    16. 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.
    17. Robert H. Porter, 1983. "A Study of Cartel Stability: The Joint Executive Committee, 1880-1886," Bell Journal of Economics, The RAND Corporation, vol. 14(2), pages 301-314, Autumn.
    18. Achim Zeileis, 2004. "Alternative boundaries for CUSUM tests," Statistical Papers, Springer, vol. 45(1), pages 123-131, January.
    19. 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.
    20. Bolotova, Yuliya & Connor, John M. & Miller, Douglas J., 2008. "The impact of collusion on price behavior: Empirical results from two recent cases," International Journal of Industrial Organization, Elsevier, vol. 26(6), pages 1290-1307, November.
    21. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    22. Kramer, Walter & Ploberger, Werner & Alt, Raimund, 1988. "Testing for Structural Change in Dynamic Models," Econometrica, Econometric Society, vol. 56(6), pages 1355-1369, November.
    23. Ploberger, Werner & Kramer, Walter, 1992. "The CUSUM Test with OLS Residuals," Econometrica, Econometric Society, vol. 60(2), pages 271-285, March.
    24. 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.
    25. Achim Zeileis & Friedrich Leisch & Christian Kleiber & Kurt Hornik, 2005. "Monitoring structural change in dynamic econometric models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 99-121, January.
    26. Leisch, Friedrich & Hornik, Kurt & Kuan, Chung-Ming, 2000. "Monitoring Structural Changes With The Generalized Fluctuation Test," Econometric Theory, Cambridge University Press, vol. 16(6), pages 835-854, December.
    27. Chu, Chia-Shang James & Hornik, Kurt & Kuan, Chung-Ming, 1995. "The Moving-Estimates Test for Parameter Stability," Econometric Theory, Cambridge University Press, vol. 11(4), pages 699-720, August.
    28. Ploberger, Werner & Kramer, Walter & Kontrus, Karl, 1989. "A new test for structural stability in the linear regression model," Journal of Econometrics, Elsevier, vol. 40(2), pages 307-318, February.
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    Cited by:

    1. H. Peter Boswijk & Maurice J. G. Bun & Maarten Pieter Schinkel, 2019. "Cartel dating," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(1), pages 26-42, January.
    2. Willem H. Boshoff & Rossouw van Jaarsveld, 2019. "Recurrent Collusion: Cartel Episodes and Overcharges in the South African Cement Market," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 54(2), pages 353-380, March.

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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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