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Data Driven Regulation: Theory and Application to Missing Bids

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  • Sylvain Chassang
  • Kei Kawai
  • Jun Nakabayashi
  • Juan M. Ortner

Abstract

We document a novel bidding pattern observed in procurement auctions from Japan: winning bids tend to be isolated. There is a missing mass of close losing bids. This pattern is suspicious in the following sense: it is inconsistent with competitive behavior under arbitrary information structures. Building on this observation, we develop a theory of data-driven regulation based on “safe tests,” i.e. tests that are passed with probability one by competitive bidders, but need not be passed by non-competitive ones. We provide a general class of safe tests exploiting weak equilibrium conditions, and show that such tests reduce the set of equilibrium strategies that cartels can use to sustain collusion. We provide an empirical exploration of various safe tests in our data, as well as discuss collusive rationales for missing bids.

Suggested Citation

  • Sylvain Chassang & Kei Kawai & Jun Nakabayashi & Juan M. Ortner, 2019. "Data Driven Regulation: Theory and Application to Missing Bids," NBER Working Papers 25654, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:25654
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    Cited by:

    1. Kory Kroft & Yao Luo & Magne Mogstad & Bradley Setzler, 2020. "Imperfect Competition and Rents in Labor and Product Markets: The Case of the Construction Industry," Working Papers tecipa-666, University of Toronto, Department of Economics.
    2. 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.
    3. 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.
    4. Francesco Decarolis & Cristina Giorgiantonio, 2020. "Corruption red flags in public procurement: new evidence from Italian calls for tenders," Questioni di Economia e Finanza (Occasional Papers) 544, Bank of Italy, Economic Research and International Relations Area.
    5. Juan Ortner & Sylvain Chassang & Jun Nakabayashi & Kei Kawai, 2020. "Screening Adaptive Cartels," Working Papers 2020-59, Princeton University. Economics Department..
    6. Huang, Yangguang, 2019. "An empirical study of scoring auctions and quality manipulation corruption," European Economic Review, Elsevier, vol. 120(C).
    7. 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.
    8. 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.
    9. David Imhof & Hannes Wallimann, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," Papers 2105.00337, arXiv.org.
    10. 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).

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    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • H57 - Public Economics - - National Government Expenditures and Related Policies - - - Procurement
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation

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