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Research Details

Persuading Statisticians

Abstract

We incorporate statistical inference into persuasion environments. A decision maker (DM), e.g. a buyer, considers whether to take a costly action. The DM does not know the action's value and relies on data and statistical inference to estimate it. Access to data, which are Bernoulli experiments governed by the action's value, is controlled by a designer who wishes the DM to take the action, e.g. a seller. In environments without transfers, the designer optimally increases the DM's data access as the degree of conflict between them decreases. In environments with transfers, the designer optimally provides minimal data access and charges a very high price.

Type

Working Paper

Author(s)

Yuval Salant, Sanket Patil

Date Published

2020

Citations

Salant, Yuval, and Sanket Patil. 2020. Persuading Statisticians.

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