Learning about informativeness

Fuente: arXiv
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Main Author: Huang, Wanying
Format: Preprint
Published: 2024
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author Huang, Wanying
author_facet Huang, Wanying
contents We study a sequential social learning model in which there is uncertainty about the informativeness of a common signal-generating process. Rational agents arrive in order and make decisions based on the past actions of others and their private signals. We show that, in this setting, asymptotic learning about informativeness is not guaranteed and depends crucially on the relative tail distributions of the private beliefs induced by uninformative and informative signals. We identify the phenomenon of perpetual disagreement as the cause of learning and characterize learning in the canonical Gaussian environment.
format Preprint
id arxiv_https___arxiv_org_abs_2406_05299
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Learning about informativeness
Huang, Wanying
Theoretical Economics
We study a sequential social learning model in which there is uncertainty about the informativeness of a common signal-generating process. Rational agents arrive in order and make decisions based on the past actions of others and their private signals. We show that, in this setting, asymptotic learning about informativeness is not guaranteed and depends crucially on the relative tail distributions of the private beliefs induced by uninformative and informative signals. We identify the phenomenon of perpetual disagreement as the cause of learning and characterize learning in the canonical Gaussian environment.
title Learning about informativeness
topic Theoretical Economics
url https://arxiv.org/abs/2406.05299