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Cited by 269

The DOI matches its Crossref record; 125 of the 125 references it cites were found in a registry or an index.

SELECTIVE ATTENTION AND LEARNING

Schwartzstein, Joshua·2014·Journal of the European Economic Association

Abstract

What do we notice and how does this affect what we learn and come to believe? I present a model of an agent who learns to make forecasts on the basis of readily available information, but is selective as to which information he attends to: he chooses whether to attend as a function of current beliefs about whether such information is predictive. If the agent does not attend to some piece of information, it cannot be recalled at a later date. He uses Bayes’ rule to update his beliefs given attended-to information, but does not attempt to fill in missing information. The model demonstrates how selective attention may lead the agent to persistently fail to recognize important empirical regularities, make systematically biased forecasts, and hold incorrect beliefs about the statistical relationship between variables. In addition, it identifies factors that make such errors more likely or persistent. The model is applied to shed light on stereotyping and discrimination, persistent learning failures and disagreement, and the process of discovery.

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Metadata

Authors
Schwartzstein, J.
Venue
Journal of the European Economic Association
Published
2014-10-03
Volume
12
Issue
6
Pages
1423-1452
ISSN
1542-4766 (ISSN-L)
OpenAlex
W1515067367
Cited by
269
References
125
FWCI
17.93
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: SELECTIVE ATTENTION AND LEARNING. https://app.cochat.ai/papers/10.1111/jeea.12104
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Schwartzstein, J. (2014). SELECTIVE ATTENTION AND LEARNING. Journal of the European Economic Association. https://doi.org/10.1111/jeea.12104

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.