Data Driven Regulation: Theory and Application to Missing Bids

55 Pages Posted: 19 Mar 2019

See all articles by Sylvain Chassang

Sylvain Chassang

New York University (NYU) - Department of Economics

Kei Kawai

University of California at Berkeley

Jun Nakabayashi

Kindai University

Juan Ortner

Boston University

Date Written: March 2019

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.

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Suggested Citation

Chassang, Sylvain and Kawai, Kei and Nakabayashi, Jun and Ortner, Juan, Data Driven Regulation: Theory and Application to Missing Bids (March 2019). NBER Working Paper No. w25654. Available at SSRN: https://ssrn.com/abstract=3354308

Sylvain Chassang (Contact Author)

New York University (NYU) - Department of Economics ( email )

19 West 4th Street
New York, NY 10012
United States

Kei Kawai

University of California at Berkeley ( email )

Berkeley, CA 94720
United States

Jun Nakabayashi

Kindai University ( email )

Kowakae 3-4-1
Higashiosaka, Osaka 522-8502
Japan

Juan Ortner

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

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