Collective Sampling: An Ex Ante Perspective

Fuente: arXiv
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Autore principale: Zhou, Yangfan
Natura: Preprint
Pubblicazione: 2023
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author Zhou, Yangfan
author_facet Zhou, Yangfan
contents I study collective dynamic information acquisition. Players decide when to stop sequential sampling via a collective stopping rule, which specifies decisive coalitions that can terminate information acquisition upon agreement. I develop a methodology to characterize equilibria using an ex ante perspective. Instead of stopping strategies, players choose distributions over posterior beliefs subject to majorization constraints. Equilibrium sampling regions are characterized via a fixed-point argument based on concavification. Collective sampling generates learning inefficiencies and having more decisive coalitions typically reduces learning. I apply the model to committee search and competition in persuasion.
format Preprint
id arxiv_https___arxiv_org_abs_2311_05758
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Collective Sampling: An Ex Ante Perspective
Zhou, Yangfan
Theoretical Economics
I study collective dynamic information acquisition. Players decide when to stop sequential sampling via a collective stopping rule, which specifies decisive coalitions that can terminate information acquisition upon agreement. I develop a methodology to characterize equilibria using an ex ante perspective. Instead of stopping strategies, players choose distributions over posterior beliefs subject to majorization constraints. Equilibrium sampling regions are characterized via a fixed-point argument based on concavification. Collective sampling generates learning inefficiencies and having more decisive coalitions typically reduces learning. I apply the model to committee search and competition in persuasion.
title Collective Sampling: An Ex Ante Perspective
topic Theoretical Economics
url https://arxiv.org/abs/2311.05758