Abstract
We consider a market for lemons in which the seller is a monopolistic price setter and the buyer receives a private noisy signal of the product’s quality. We model this as a game and analyze perfect Bayesian equilibrium prices, trading probabilities and gains of trade. In particular, we vary the buyer’s signal precision, from being completely uninformative, as in standard models of lemons markets, to being perfectly informative. We show that high quality units are sold with positive probability even in the limit of uninformative signals, and we identify some discontinuities in the equilibrium predictions at the boundaries of completely uninformative and completely informative signals, respectively.
Highlights
In many markets, prospective buyers are imperfectly informed about the quality of the items for sale
A used-car owner usually knows more about his car than the prospective buyer and a job applicant usually knows more about her ability than the employer
Recalling that the set P0 of pooling equilibrium prizes in this limit case is empty if wH > vand non-empty if wH < v, we focus on the latter case
Summary
Prospective buyers are imperfectly informed about the quality of the items for sale. On the other hand, often know much about the quality of their products. In his classical “market for lemons” paper, George Akerlof showed that such informational asymmetry, when taken to the extreme, can lead to adverse selection. That paper initiated a surge of economic analyses of markets with asymmetric information, where typically the seller has better information than the buyer. A used-car owner usually knows more about his car than the prospective buyer and a job applicant usually knows more about her ability than the employer.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
