Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/320247 
Year of Publication: 
2024
Citation: 
[Journal:] Theoretical Economics [ISSN:] 1555-7561 [Volume:] 19 [Issue:] 2 [Year:] 2024 [Pages:] 583-604
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
A statistical decision rule is a mapping from data to actions induced by statistical inference on the data. We characterize these rules for data that are chosen strategically in persuasion environments. A designer wishes to persuade a decision maker (DM) to take a particular action and decides how many Bernoulli experiments about a parameter of interest the DM can obtain. After obtaining these data and estimating the parameter value, the DM chooses to take the action if the estimated value exceeds some threshold. We establish that as the threshold changes, the resulting statistical decision rules in many environments are either simple majority or reverse unanimity.
Subjects: 
persuasion
sample size
statistical decision rule
Statistical inference
JEL: 
C90
D81
D83
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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