IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_12073.html
   My bibliography  Save this paper

Detection of Collusive Networks in Multistage Auctions

Author

Listed:
  • Bruno Baránek
  • Leon Musolff
  • Vitezslav Titl

Abstract

We develop a method for detecting cartels in multistage auctions. Our approach allows a firm to be collusive when facing members of its cartel yet competitive when facing others. Intuitively, as initial bids are shaded, close initial bids not only imply similar costs but also provide an incentive to undercut. We detect firm pairs that ignore this incentive when facing each other. Our algorithm predicts Ukraine’s Antimonopoly Committee’s sanctions: firm pairs classified as collusive are 8.98 times more likely (standard error 2.65 times) to be sanctioned. It also uncovers additional collusion: 1,857 collusive firms participate in 15.57% of auctions, increasing costs by 1.95%.

Suggested Citation

  • Bruno Baránek & Leon Musolff & Vitezslav Titl, 2025. "Detection of Collusive Networks in Multistage Auctions," CESifo Working Paper Series 12073, CESifo.
    • Handle: RePEc:ces:ceswps:_12073
    as

    Download full text from publisher

    File URL: https://www.ifo.de/DocDL/cesifo1_wp12073.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Clark, Robert & Coviello, Decio & de Leverano, Adriano, 2020. "Complementary bidding and the collusive arrangement: Evidence from an antitrust investigation," ZEW Discussion Papers 20-052, ZEW - Leibniz Centre for European Economic Research.
    2. Erica Bosio & Simeon Djankov & Edward Glaeser & Andrei Shleifer, 2022. "Public Procurement in Law and Practice," American Economic Review, American Economic Association, vol. 112(4), pages 1091-1117, April.
    3. Sean Lewis-Faupel & Yusuf Neggers & Benjamin A. Olken & Rohini Pande, 2016. "Can Electronic Procurement Improve Infrastructure Provision? Evidence from Public Works in India and Indonesia," American Economic Journal: Economic Policy, American Economic Association, vol. 8(3), pages 258-283, August.
    4. Maxim Mironov & Ekaterina Zhuravskaya, 2016. "Corruption in Procurement and the Political Cycle in Tunneling: Evidence from Financial Transactions Data," American Economic Journal: Economic Policy, American Economic Association, vol. 8(2), pages 287-321, May.
    5. Kei Kawai & Jun Nakabayashi & Juan Ortner & Sylvain Chassang, 2023. "Using Bid Rotation and Incumbency to Detect Collusion: A Regression Discontinuity Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(1), pages 376-403.
    6. 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.
    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. Bruno Baránek & Vítězslav Titl, 2024. "The Cost of Favoritism in Public Procurement," Journal of Law and Economics, University of Chicago Press, vol. 67(2), pages 445-477.
    9. Michael K. Price, 2008. "Using The Spatial Distribution Of Bidders To Detect Collusion In The Marketplace: Evidence From Timber Auctions," Journal of Regional Science, Wiley Blackwell, vol. 48(2), pages 399-417, May.
    10. John Asker, 2010. "A Study of the Internal Organization of a Bidding Cartel," American Economic Review, American Economic Association, vol. 100(3), pages 724-762, June.
    11. Maria Paula Gerardino & Stephan Litschig & Dina Pomeranz, 2024. "Distortion by Audit: Evidence from Public Procurement," American Economic Journal: Applied Economics, American Economic Association, vol. 16(4), pages 71-108, October.
    12. Fibich, Gadi & Gavish, Nir, 2011. "Numerical simulations of asymmetric first-price auctions," Games and Economic Behavior, Elsevier, vol. 73(2), pages 479-495.
    13. Martin Pesendorfer, 2000. "A Study of Collusion in First-Price Auctions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 67(3), pages 381-411.
    14. Sylvain Chassang & Juan Ortner, 2019. "Collusion in Auctions with Constrained Bids: Theory and Evidence from Public Procurement," Journal of Political Economy, University of Chicago Press, vol. 127(5), pages 2269-2300.
    15. 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.
    16. Svend Albæk & Peter Møllgaard & Per B. Overgaard, 1997. "Government‐Assisted Oligopoly Coordination? A Concrete Case," Journal of Industrial Economics, Wiley Blackwell, vol. 45(4), pages 429-443, December.
    17. Sylvain Chassang & Kei Kawai & Jun Nakabayashi & Juan Ortner, 2022. "Robust Screens for Noncompetitive Bidding in Procurement Auctions," Econometrica, Econometric Society, vol. 90(1), pages 315-346, January.
    18. Benjamin A. Olken, 2007. "Monitoring Corruption: Evidence from a Field Experiment in Indonesia," Journal of Political Economy, University of Chicago Press, vol. 115(2), pages 200-249.
    19. David Schoenherr, 2019. "Political Connections and Allocative Distortions," Journal of Finance, American Finance Association, vol. 74(2), pages 543-586, April.
    20. Timothy G. Conley & Francesco Decarolis, 2016. "Detecting Bidders Groups in Collusive Auctions," American Economic Journal: Microeconomics, American Economic Association, vol. 8(2), pages 1-38, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Niuniu Zhang, 2025. "Too Noisy to Collude? Algorithmic Collusion Under Laplacian Noise," Papers 2509.02800, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martin, Julien & Pesendorfer, Martin & Shannon, Jack, 2025. "Underbidding for oil and gas tracts," LSE Research Online Documents on Economics 128285, London School of Economics and Political Science, LSE Library.
    2. Granlund, David & Rudholm, Niklas, 2023. "Calculating the probability of collusion based on observed price patterns," Umeå Economic Studies 1014, Umeå University, Department of Economics, revised 13 Oct 2023.
    3. Clark, Robert & Coviello, Decio & de Leverano, Adriano, 2020. "Complementary bidding and the collusive arrangement: Evidence from an antitrust investigation," ZEW Discussion Papers 20-052, ZEW - Leibniz Centre for European Economic Research.
    4. Robert Clark & Decio Coviello & Jean-Fran�ois Gauthier & Art Shneyerov, 2018. "Bid Rigging and Entry Deterrence in Public Procurement: Evidence from an Investigation into Collusion and Corruption in Quebec," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 34(3), pages 301-363.
    5. de Leverano, Adriano, 2019. "Collusion through market sharing agreements: Evidence from Quebec's road paving market," ZEW Discussion Papers 19-053, ZEW - Leibniz Centre for European Economic Research.
    6. 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.
    7. Bruno Baranek & L. Musolff & Vitezslav Titl, 2021. "Detection of Collusive Networks in E-procurement," Working Papers 2111, Utrecht School of Economics.
    8. Aaltio, Aapo & Buri, Riku & Jokelainen, Antto & Lundberg, Johan, 2025. "Complementary bidding and cartel detection: Evidence from Nordic asphalt markets," International Journal of Industrial Organization, Elsevier, vol. 98(C).
    9. Sylvain Chassang & Kei Kawai & Jun Nakabayashi & Juan Ortner, 2019. "Data Driven Regulation: Theory and Application to Missing Bids," Boston University - Department of Economics - Working Papers Series WP2019-04, Boston University - Department of Economics.
    10. Gabrielli, M. Florencia & Willington, Manuel, 2023. "Estimating damages from bidding rings in first-price auctions," Economic Modelling, Elsevier, vol. 126(C).
    11. David Barrus & Frank Scott, 2020. "Single Bidders and Tacit Collusion in Highway Procurement Auctions," Journal of Industrial Economics, Wiley Blackwell, vol. 68(3), pages 483-522, September.
    12. Lu, Jiaxuan, 2023. "The economics of China’s between-city height competition: A regression discontinuity approach," Regional Science and Urban Economics, Elsevier, vol. 100(C).
    13. 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).
    14. Kei Kawai & Jun Nakabayashi & Juan Ortner & Sylvain Chassang, 2023. "Using Bid Rotation and Incumbency to Detect Collusion: A Regression Discontinuity Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(1), pages 376-403.
    15. David Imhof & Emanuel W Viklund & Martin Huber, 2025. "Catching Bid-rigging Cartels with Graph Attention Neural Networks," Papers 2507.12369, arXiv.org, revised Jul 2025.
    16. Johannes Wachs & J'anos Kert'esz, 2019. "A network approach to cartel detection in public auction markets," Papers 1906.08667, arXiv.org.
    17. Bernasconi, Mario, 2024. "Essays on labour economics and industrial organization," Other publications TiSEM c26b3dfe-a2d3-4c31-b0fc-f, Tilburg University, School of Economics and Management.
    18. Robert Clark & Ignatius Horstmann & Jean-François Houde, 2021. "Hub and Spoke Cartels: Theory and Evidence from the Grocery Industry," NBER Working Papers 29253, National Bureau of Economic Research, Inc.
    19. 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.
    20. Ilke Onur & Bedri Kamil Onur Tas, 2019. "Optimal bidder participation in public procurement auctions," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(3), pages 595-617, June.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • H57 - Public Economics - - National Government Expenditures and Related Policies - - - Procurement
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_12073. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.