IDEAS home Printed from https://ideas.repec.org/a/eee/indorg/v98y2025ics0167718724000845.html
   My bibliography  Save this article

Complementary bidding and cartel detection: Evidence from Nordic asphalt markets

Author

Listed:
  • Aaltio, Aapo
  • Buri, Riku
  • Jokelainen, Antto
  • Lundberg, Johan

Abstract

A key challenge in cartel enforcement is identifying collusive agreements. We study two major Nordic procurement cartels that operated in the asphalt paving market. We find evidence that during the cartel period bids were clustered and the winning bid was isolated. We implement two cartel detection methods that exploit variation in the distribution of bids. The method developed by Clark et al. (forthcoming) correctly rejects competitive bidding for the cartel period in both markets. The method suggested by Huber and Imhof (2019) achieves a high prediction rate in one of the markets but not in the market where the cartel had a more modest impact on bid distribution. Our results suggest that statistical screening methods with low data requirements can be useful for competition authorities in detecting collusive agreements.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:indorg:v:98:y:2025:i:c:s0167718724000845
    DOI: 10.1016/j.ijindorg.2024.103129
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167718724000845
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijindorg.2024.103129?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Johan Lundberg, 2017. "On cartel detection and Moran’s I," Letters in Spatial and Resource Sciences, Springer, vol. 10(1), pages 129-139, March.
    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. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    4. Kei Kawai & Jun Nakabayashi & Daichi Shimamoto, 2022. "A Study of Bid-rigging in Procurement Auctions: Evidence from Indonesia, Georgia, Mongolia, Malta, and State of California," NBER Working Papers 30271, National Bureau of Economic Research, Inc.
    5. Feinstein, Jonathan S & Block, Michael K & Nold, Frederick C, 1985. "Asymmetric Information and Collusive Behavior in Auction Markets," American Economic Review, American Economic Association, vol. 75(3), pages 441-460, June.
    6. Bryant, Peter G & Eckard, E Woodrow, Jr, 1991. "Price Fixing: The Probability of Getting Caught," The Review of Economics and Statistics, MIT Press, vol. 73(3), pages 531-536, August.
    7. Bruno Baranek & L. Musolff & Vitezslav Titl, 2021. "Detection of Collusive Networks in E-procurement," Working Papers 2111, Utrecht School of Economics.
    8. 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).
    9. 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.
    10. Emmanuel Combe & Constance Monnier & Renaud Legal, 2008. "Cartels: The Probability of Getting Caught in the European Union," Bruges European Economic Research Papers 12, European Economic Studies Department, College of Europe.
    11. 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.
    12. Aryal, Gaurab & Gabrielli, Maria F., 2013. "Testing for collusion in asymmetric first-price auctions," International Journal of Industrial Organization, Elsevier, vol. 31(1), pages 26-35.
    13. Joseph E. HarringtonJr. & Yanhao Wei, 2017. "What Can the Duration of Discovered Cartels Tell Us About the Duration of All Cartels?," Economic Journal, Royal Economic Society, vol. 127(604), pages 1977-2005.
    14. Jääskeläinen, Jan & Tukiainen, Janne, 2019. "Anatomy of public procurement," Working Papers 118, VATT Institute for Economic Research.
    15. 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.
    16. Marcel Boyer & Rachidi Kotchoni, 2015. "How Much Do Cartel Overcharge?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 47(2), pages 119-153, September.
    17. Mats A. Bergman & Johan Lundberg & Sofia Lundberg & Johan Y. Stake, 2020. "Interactions Across Firms and Bid Rigging," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 56(1), pages 107-130, February.
    18. 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).
    19. De Leverano, Adriano, 2023. "Clustered bids in first-price auctions: Collusion or competition?," Economics Letters, Elsevier, vol. 233(C).
    20. Claudio Ferraz & Frederico Finan & Dimitri Szerman, 2015. "Procuring Firm Growth: The Effects of Government Purchases on Firm Dynamics," NBER Working Papers 21219, National Bureau of Economic Research, Inc.
    21. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    22. Decio Coviello & Stefano Gagliarducci, 2017. "Tenure in Office and Public Procurement," American Economic Journal: Economic Policy, American Economic Association, vol. 9(3), pages 59-105, August.
    23. Joseph E. Harrington Jr. & Yanhao Wei, 2017. "What Can the Duration of Discovered Cartels Tell Us About the Duration of All Cartels?," Economic Journal, Royal Economic Society, vol. 127(604), pages 1977-2005, September.
    24. 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.
    25. 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.
    26. Audinga Baltrunaite, 2020. "Political Contributions and Public Procurement: Evidence from Lithuania," Journal of the European Economic Association, European Economic Association, vol. 18(2), pages 541-582.
    27. 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.
    28. 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).
    29. Chantale LaCasse, 1995. "Bid Rigging and the Threat of Government Prosecution," RAND Journal of Economics, The RAND Corporation, vol. 26(3), pages 398-417, Autumn.
    30. Nicole M. Fortin & Thomas Lemieux & Neil Lloyd, 2021. "Labor Market Institutions and the Distribution of Wages: The Role of Spillover Effects," Journal of Labor Economics, University of Chicago Press, vol. 39(S2), pages 369-412.
    31. 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.
    32. 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.
    33. Ailin Dong & Massimo Massa & Alminas Žaldokas, 2019. "The effects of global leniency programs on margins and mergers," RAND Journal of Economics, RAND Corporation, vol. 50(4), pages 883-915, December.
    34. Bolotova, Yuliya V., 2009. "Cartel overcharges: An empirical analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 321-341, May.
    35. David Imhof & Hannes Wallimann, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," Papers 2105.00337, arXiv.org.
    36. Leonardo M. Giuffrida & Gabriele Rovigatti, 2022. "Supplier selection and contract enforcement: Evidence from performance bonding," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(4), pages 980-1019, November.
    37. Patrick Bajari & Stephanie Houghton & Steven Tadelis, 2014. "Bidding for Incomplete Contracts: An Empirical Analysis of Adaptation Costs," American Economic Review, American Economic Association, vol. 104(4), pages 1288-1319, April.
    38. Connor, John M. & Bolotova, Yuliya, 2006. "Cartel overcharges: Survey and meta-analysis," International Journal of Industrial Organization, Elsevier, vol. 24(6), pages 1109-1137, November.
    39. Kei Kawai & Jun Nakabayashi, 2022. "Detecting Large-Scale Collusion in Procurement Auctions," Journal of Political Economy, University of Chicago Press, vol. 130(5), pages 1364-1411.
    40. Marcel Boyer & Rachidi Kotchoni, 2015. "How Much Do Cartel Overcharge? (The "Working Paper" Version)," CIRANO Working Papers 2015s-37, CIRANO.
    41. David Imhof & Yavuz Karagök & Samuel Rutz, 2018. "Screening For Bid Rigging—Does It Work?," Journal of Competition Law and Economics, Oxford University Press, vol. 14(2), pages 235-261.
    42. 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)

    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. 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.
    2. 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).
    3. Silveira, Douglas & de Moraes, Lucas B. & Fiuza, Eduardo P.S. & Cajueiro, Daniel O., 2023. "Who are you? Cartel detection using unlabeled data," International Journal of Industrial Organization, Elsevier, vol. 88(C).
    4. 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.
    5. 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).
    6. Johannes Wachs & J'anos Kert'esz, 2019. "A network approach to cartel detection in public auction markets," Papers 1906.08667, arXiv.org.
    7. Hannes Wallimann & Silvio Sticher, 2023. "On suspicious tracks: machine-learning based approaches to detect cartels in railway-infrastructure procurement," Papers 2304.11888, arXiv.org.
    8. Bedri Kamil Onur Tas, 2024. "A machine learning approach to detect collusion in public procurement with limited information," Journal of Computational Social Science, Springer, vol. 7(2), pages 1913-1935, October.
    9. 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.
    10. Wallimann, Hannes & Sticher, Silvio, 2023. "On suspicious tracks: Machine-learning based approaches to detect cartels in railway-infrastructure procurement," Transport Policy, Elsevier, vol. 143(C), pages 121-131.
    11. Brown, David P. & Eckert, Andrew & Silveira, Douglas, 2023. "Screening for collusion in wholesale electricity markets: A literature review," Utilities Policy, Elsevier, vol. 85(C).
    12. 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.
    13. David Imhof & Hannes Wallimann, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," Papers 2105.00337, arXiv.org.
    14. 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.
    15. 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.
    16. 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.
    17. 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).
    18. Huang, Yangguang, 2019. "An empirical study of scoring auctions and quality manipulation corruption," European Economic Review, Elsevier, vol. 120(C).
    19. Gabrielli, M. Florencia & Willington, Manuel, 2023. "Estimating damages from bidding rings in first-price auctions," Economic Modelling, Elsevier, vol. 126(C).
    20. Mats A. Bergman & Johan Lundberg & Sofia Lundberg & Johan Y. Stake, 2020. "Interactions Across Firms and Bid Rigging," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 56(1), pages 107-130, February.

    More about this item

    Keywords

    Procurement; Bidding ring; Collusion; Antitrust; Complementary bidding; Detection;
    All these keywords.

    JEL classification:

    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure
    • L74 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Construction
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • H57 - Public Economics - - National Government Expenditures and Related Policies - - - Procurement

    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:eee:indorg:v:98:y:2025:i:c:s0167718724000845. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505551 .

    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.