Slope Takers in Anonymous Markets

Daniel Quint and Marek Weretka

American Economic Journal: Microeconomics, 2023, vol. 15, issue 4, 306-18

Abstract: We present a learning-based selection argument for Linear Bayesian Nash equilibrium in a Walrasian auction. Endowments vary stochastically; traders model residual supply as linear, estimate its slope from past trade data, and periodically update these estimates. In the standard setting with quadratic preferences, we show that this learning process converges to the unique LBN. Anonymity and statistical learning therefore support this commonly used equilibrium selection rule.

JEL-codes: D43 D44 D83 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.aeaweb.org/doi/10.1257/mic.20220078 (application/pdf)
https://doi.org/10.3886/E179101V1 (text/html)
https://www.aeaweb.org/doi/10.1257/mic.20220078.ds (application/zip)
Access to full text is restricted to AEA members and institutional subscribers.

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:aea:aejmic:v:15:y:2023:i:4:p:306-18

Ordering information: This journal article can be ordered from
https://www.aeaweb.org/journals/subscriptions

DOI: 10.1257/mic.20220078

Access Statistics for this article

American Economic Journal: Microeconomics is currently edited by Johannes Hörner

More articles in American Economic Journal: Microeconomics from American Economic Association Contact information at EDIRC.
Bibliographic data for series maintained by Michael P. Albert ().