Inertia in social learning from a summary statistic

Nathan Larson

MPRA Paper from University Library of Munich, Germany

Abstract: We model normal-quadratic social learning with agents who observe a summary statistic over past actions, rather than complete action histories. Because an agent with a summary statistic cannot correct for the fact that earlier actions influenced later ones, even a small presence of old actions in the statistic can introduce very persistent errors. Depending on how fast these old actions fade from view, social learning can either be as fast as if agents’ private information were pooled (rate n) or it can slow to a crawl (rate ln n). We also examine extensions to learning from samples of actions, learning about a moving target, heterogeneous preferences, and biases toward own information.

Keywords: social learning; herding; speed of learning (search for similar items in EconPapers)
JEL-codes: D81 D83 (search for similar items in EconPapers)
Date: 2008, Revised 2011-07
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Journal Article: Inertia in social learning from a summary statistic (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:32143

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