Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/296453 
Authors: 
Year of Publication: 
2024
Citation: 
[Journal:] Theoretical Economics [ISSN:] 1555-7561 [Volume:] 19 [Issue:] 1 [Year:] 2024 [Pages:] 29-60
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
We study the interaction between an agent of uncertain type, whose project gives rise to both good and bad news, and an evaluator who must decide if and when to fire the agent. The agent can hide bad news from the evaluator at some cost, and will do so if this secures her a significant increase in tenure. When bad news is conclusive, censorship hurts the evaluator, the good agent, and possibly the bad agent. However, when bad news is inconclusive, censorship may benefit all those players. This is because the good agent censors bad news more aggressively than the bad agent, which improves the quality of information.
Subjects: 
Censorship
dynamic games
information manipulation
learning
JEL: 
C73
D82
D83
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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