arrow
Return

I Don't Know

delete2020-08-01
delete7
PRE
AI
M
Matthew Backus *
A
Andrew T. Little
DOI:10.1017/S0003055420000209delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Political decision makers make choices in a complex and uncertain world, where even the most qualified experts may not know what policies will succeed. Worse, if these experts care about their reputation for competence, they may be averse to admitting what they don't know. We model the strategic communication of uncertainty, allowing for the salient reality that sometimes the effects of proposed policies are impossible to know. Our model highlights the challenge of getting experts to admit uncertainty, even when it is possible to check predictive success. Moreover, we identify a novel solution: checking features of the question that only good experts will infer-in particular, whether the effect of policies is knowable-can induce uninformed experts do say I Don't Know.
Keywords:
DYNAMIC OLIGOPOLY
INFORMATION
COMPETITION
COMMUNICATION
DISCLOSURE
MODEL
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

American Political Science Review cover
American Political Science Review
IF:
5.8
Papers:
8.7K
Citations:
2.1W

Organization

C
Columbia University
Scholars:
7.1W
Papers: 6.4W
Citations: 263
University of California System cover
University of California System
Scholars:
37.5W
Papers: 33.7W
Citations: 6.6K