Bargaining under the Illusion of Transparency

Kristóf Madarász

American Economic Review, 2021, vol. 111, issue 11, 3500-3539

Abstract: This paper studies bargaining with noncommon priors where the buyer projects and exaggerates the probability that her private information may leak to the seller. Letting the buyer name her price first, raises the seller's payoff above his payoff from posting a price. In seller-offer bargaining, projection implies a partial reversal of classic Coasian comparative static results. Weakening price commitment can benefit the seller and, as long as the relative speed at which imaginary information versus offers arrive does not converge to zero too quickly, frictionless bargaining converges to a fast haggling process which allows the seller to extract all surplus from trade. Bargaining under common prior transparency is instead slow and becomes equivalent to simply waiting. The comparative static predictions are consistent with experimental evidence.

JEL-codes: C78 D82 (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.aeaweb.org/doi/10.1257/aer.20150004 (application/pdf)
https://www.aeaweb.org/doi/10.1257/aer.20150004.appx (application/pdf)
https://www.aeaweb.org/doi/10.1257/aer.20150004.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:aecrev:v:111:y:2021:i:11:p:3500-3539

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

DOI: 10.1257/aer.20150004

Access Statistics for this article

American Economic Review is currently edited by Esther Duflo

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