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SSRN Electronic Journal
Article . 2017 . Peer-reviewed
Data sources: Crossref
EconStor
Research . 2016
Data sources: EconStor
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Competing Mechanisms with Limited Commitment

Authors: Kwon, Suehyun;

Competing Mechanisms with Limited Commitment

Abstract

This paper studies competing mechanisms with limited commitment over infinite horizon. Between a mechanism and the agent, there is perfect monitoring, but each mechanism can have arbitrary signals about the interaction between other mechanisms and the agent. I show that if the agent’s type is common knowledge, any individually rational payoffs can be sustained in a perfect Bayesian equilibrium. If the agent’s type is his private information, Pareto frontier of mechanisms’ payoffs can be obtained by repeating the static optimal screening every period; in particular, price posting with the static optimal price is the optimal mechanism. The complete information case is a strong form of folk theorem while the incomplete information case shows that folk theorem breaks down with private information even as the discount factor goes to one. Results hold with any finite number of mechanisms, any discount factor and any monitoring technology including private monitoring.

Keywords

limited commitment, folk theorem, ddc:330, price posting, competing mechanisms, private monitoring

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
bronze