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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
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    JEL classification:

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

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