Information Asymmetries in Common-Value Auctions with Discrete Signals

47 Pages Posted: 23 Apr 2013 Last revised: 26 Jan 2014

Vasilis Syrgkanis

Microsoft Corporation - Microsoft Research New England

David Kempe

University of Southern California - Department of Computer Science

Eva Tardos

Cornell University - Department of Computer Science

Date Written: April 22, 2013

Abstract

We consider common-value hybrid auctions among two asymmetrically informed bidders, where the winning bidder pays his bid with some positive probability k and the losing bid otherwise. Under the assumption of discrete and affiliated signals, we give an explicit characterization of the (unique) equilibrium, based on a simple recurrence relation. We show that equilibrium revenue is decreasing in k, and that the limit second-price equilibrium that is selected entails extensive free-riding by uninformed bidders. We further show that the Linkage Principle can fail to hold even in a pure first-price auction with binary signals: public revelation of a signal to both bidders may decrease the auctioneer's revenue. Lastly, we analyze the effects of public acquisition of additional information on bidder utilities and exhibit cases in which both bidders strictly prefer for a specific bidder to receive additional information.

Keywords: common value, asymmetric information, revenue ranking, failure of linkage principle

JEL Classification: D44, D82, C72

Suggested Citation

Syrgkanis, Vasilis and Kempe, David and Tardos, Eva, Information Asymmetries in Common-Value Auctions with Discrete Signals (April 22, 2013). Available at SSRN: https://ssrn.com/abstract=2255268 or http://dx.doi.org/10.2139/ssrn.2255268

Vasilis Syrgkanis (Contact Author)

Microsoft Corporation - Microsoft Research New England ( email )

One Memorial Drive, 14th Floor
Cambridge, MA 02142
United States

David Kempe

University of Southern California - Department of Computer Science ( email )

Los Angeles, CA 90089-0781
United States

Eva Tardos

Cornell University - Department of Computer Science ( email )

4130 Upson Hall
Ithaca, NY 14853
United States

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