Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Information disclosure by a seller in sequential first-price auctions

Azacis, Helmuts ORCID: https://orcid.org/0000-0002-6061-2100 2020. Information disclosure by a seller in sequential first-price auctions. International Journal of Game Theory 49 , pp. 411-444. 10.1007/s00182-020-00710-8

[thumbnail of Azacis IJGT20 Information disclosure by a seller in sequential first-price auctions.pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (644kB) | Preview

Abstract

I study sequential first-price auctions where two items are sold to two bidders with private binary valuations. A seller, prior to the second auction, can publicly disclose some information about the outcome of the first auction. I characterize equilibrium strategies for various disclosure rules when the valuations of bidders are either perfectly positively or perfectly negatively correlated across items. I establish outcome equivalence between different disclosure rules. I find that it is optimal for the seller to disclose some information when the valuations are negatively correlated, whereas it is optimal not to disclose any information when the valuations are positively correlated. For most of the parameter values, the seller’s expected revenue is higher if the losing bid is disclosed. When only the winner’s identity is disclosed, the equilibrium is efficient whether the valuations are positively or negatively correlated.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Publisher: Springer
ISSN: 0020-7276
Date of First Compliant Deposit: 20 January 2020
Date of Acceptance: 10 December 2019
Last Modified: 17 Nov 2024 21:00
URI: https://orca.cardiff.ac.uk/id/eprint/128818

Citation Data

Cited 3 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics