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Cartel Detection in Procurement Markets

Author

Listed:
  • Kai Hüschelrath
  • Tobias Veith

Abstract

Cartel detection is usually viewed as a key task of either competition authorities or compliance officials in firms with an elevated risk of cartelization. We argue that customers of hard‐core cartels can have both incentives and possibilities to detect such agreements on their own initiative through the use of market‐specific datasets. We apply a unique dataset of about 340,000 market transactions from 36 smaller and larger customers of German cement producers and show that a price screen would have allowed particularly larger customers to detect the upstream cement cartel before the competition authority. Copyright © 2013 John Wiley & Sons, Ltd.

Suggested Citation

  • 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.
    • Handle: RePEc:wly:mgtdec:v:35:y:2014:i:6:p:404-422
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    Cited by:

    1. Harrington, Joseph E. & Hüschelrath, Kai & Laitenberger, Ulrich & Smuda, Florian, 2015. "The discontent cartel member and cartel collapse: The case of the German cement cartel," International Journal of Industrial Organization, Elsevier, vol. 42(C), pages 106-119.
    2. Matthias Hunold & Kai Hüschelrath & Ulrich Laitenberger & Johannes Muthers, 2020. "Competition, Collusion, and Spatial Sales Patterns: Theory and Evidence," Journal of Industrial Economics, Wiley Blackwell, vol. 68(4), pages 737-779, December.
    3. Hannes Wallimann & David Imhof & Martin Huber, 2023. "A Machine Learning Approach for Flagging Incomplete Bid-Rigging Cartels," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1669-1720, December.
    4. Hüschelrath, Kai & Müller, Kathrin & Veith, Tobias, 2012. "Estimating damages from price-fixing: The value of transaction data," ZEW Discussion Papers 12-036, ZEW - Leibniz Centre for European Economic Research.
    5. Johannes Wachs & J'anos Kert'esz, 2019. "A network approach to cartel detection in public auction markets," Papers 1906.08667, arXiv.org.
    6. Hüschelrath, Kai & Veith, Tobias, 2011. "The impact of cartelization on pricing dynamics: Evidence from the German cement industry," ZEW Discussion Papers 11-067, ZEW - Leibniz Centre for European Economic Research.
    7. Clara Calini & Alessandra Catenazzo & Elisabetta Iossa, 2025. "Using Multiple Tools to Enhance Competition in Public Procurement," CEIS Research Paper 594, Tor Vergata University, CEIS, revised 25 Feb 2025.
    8. Imhof, David & Wallimann, Hannes, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," International Review of Law and Economics, Elsevier, vol. 68(C).
    9. Korbinian von Blanckenburg & Marc Hanfeld & Konstantin A. Kholodilin, 2013. "A Market Screening Model for Price Inconstancies: Empirical Evidence from German Electricity Markets," Discussion Papers of DIW Berlin 1274, DIW Berlin, German Institute for Economic Research.
    10. Huber, Martin & Imhof, David, 2019. "Machine learning with screens for detecting bid-rigging cartels," International Journal of Industrial Organization, Elsevier, vol. 65(C), pages 277-301.
    11. 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.
    12. 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.
    13. 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..
    14. Bedri Kamil Onur Tas, 2017. "Collusion Detection in Public Procurement with Limited Information," Working Papers 1127, Economic Research Forum, revised 08 Oct 2017.
    15. David Imhof & Hannes Wallimann, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," Papers 2105.00337, arXiv.org.
    16. Martin Huber & David Imhof & Rieko Ishii, 2022. "Transnational machine learning with screens for flagging bid‐rigging cartels," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1074-1114, July.
    17. Huber, Martin & Imhof, David, 2023. "Flagging cartel participants with deep learning based on convolutional neural networks," International Journal of Industrial Organization, Elsevier, vol. 89(C).

    More about this item

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices
    • L61 - Industrial Organization - - Industry Studies: Manufacturing - - - Metals and Metal Products; Cement; Glass; Ceramics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • K21 - Law and Economics - - Regulation and Business Law - - - Antitrust Law

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