Learning to Bid: The Design of Auctions Under Uncertainty and Adaptation

23 Pages Posted: 7 Jun 2005

See all articles by Thomas H. Noe

Thomas H. Noe

University of Oxford - Said Business School; University of Oxford - Balliol College; Bank of Finland; European Corporate Governance Institute

Michael J. Rebello

University of Texas at Dallas - Naveen Jindal School of Management

Jun Wang

City University of New York, Baruch College - Zicklin School of Business - Department of Economics and Finance

Date Written: June 2005

Abstract

We examine auction design in a context where symmetrically informed buyers and sellers of a good with a common but uncertain value learn through experience. Buyer strategies, even in the very long run, do not converge to the Bertrand-Nash strategy of bidding the expected value of the good. Moreover, first- and second-price auctions are not revenue equivalent. The outcomes of the auctions are sensitive to both the number of participating bidders and the reservation price. When only a small number of bidders participate, the sellers tend to employ a first-price auction even though it generates a lower average revenue than a second-price auction.

Keywords: Auction design, adaptive learning, genetic algorithm

JEL Classification: D44, D83

Suggested Citation

Noe, Thomas H. and Rebello, Michael J. and Wang, Jun, Learning to Bid: The Design of Auctions Under Uncertainty and Adaptation (June 2005). Available at SSRN: https://ssrn.com/abstract=738584 or http://dx.doi.org/10.2139/ssrn.738584

Thomas H. Noe (Contact Author)

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 3BJ
United Kingdom

University of Oxford - Balliol College ( email )

Broad St
Oxford, OX1 3BJ
United Kingdom

Bank of Finland ( email )

P.O. Box 160
FIN-00101 Helsinki
Finland

European Corporate Governance Institute ( email )

c/o the Royal Academies of Belgium
Rue Ducale 1 Hertogsstraat
1000 Brussels
Belgium

Michael J. Rebello

University of Texas at Dallas - Naveen Jindal School of Management ( email )

P.O. Box 830688
Richardson, TX 75083-0688
United States

Jun Wang

City University of New York, Baruch College - Zicklin School of Business - Department of Economics and Finance ( email )

17 Lexington Avenue
New York, NY 10010
United States

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