Learning to Set the Reserve Price Optimally in Laboratory First Price Auctions

Priyodorshi Banerjee, Shashwat Khare and P. Srikant
Additional contact information
Priyodorshi Banerjee: Economic Research Unit, Indian Statistical Institute, Baranagar, Kolkata, West Bengal 700108, India
Shashwat Khare: School of Business and Economics, Maastricht University, 6211 LK Maastricht, The Netherlands
P. Srikant: Madras School of Economics, Chennai, Tamil Nadu 600025, India

Games, 2018, vol. 9, issue 4, 1-16

Abstract: We analyze choices of sellers, each setting a reserve price in a laboratory first price auction with automated equilibrium bidding. Subjects are allowed to gain experience for a fixed period of time prior to making a single payoff-relevant choice. Behavior of more experienced sellers was consistent with benchmark theory: average reserve price for these sellers was independent of the number of bidders and equaled the predicted level. Less experienced sellers however deviated from the theoretical benchmark: on average, they tended to shade reserve price below the predicted level and positively relate it to the number of bidders.

Keywords: reserve price; first-price auction; experience; seller learning (search for similar items in EconPapers)
JEL-codes: C C7 C70 C71 C72 C73 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2073-4336/9/4/79/pdf (application/pdf)
https://www.mdpi.com/2073-4336/9/4/79/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jgames:v:9:y:2018:i:4:p:79-:d:174303

Access Statistics for this article

Games is currently edited by Ms. Susie Huang

More articles in Games from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().