Observational Learning with Position Uncertainty

Ignacio Monzon and Michael Rapp

No 206, Carlo Alberto Notebooks from Collegio Carlo Alberto

Abstract: Observational learning is typically examined when agents have precise information about their position in the sequence of play. We present a model in which agents are uncertain about their positions. Agents are allowed to have arbitrary ex-ante beliefs about their positions: they may observe their position perfectly, imperfectly, or not at all. Agents sample the decisions of past individuals and receive a private signal about the state of the world. We show that social learning is robust to position uncertainty. Under any sampling rule satisfying a stationarity assumption, learning is complete if signal strength is unbounded. In cases with bounded signal strength, we show that agents achieve what we define as constrained efficient learning: individuals do at least as well as the most informed agent would do in isolation.

Keywords: social learning; information aggregation; herds; position uncertainty; observational learning (search for similar items in EconPapers)
JEL-codes: C72 D83 D85 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2011
New Economics Papers: this item is included in nep-cba, nep-cta and nep-gth
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Journal Article: Observational learning with position uncertainty (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:cca:wpaper:206

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