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Article: Learning from a Black Box

TitleLearning from a Black Box
Authors
Issue Date8-Aug-2024
PublisherElsevier
Citation
Journal of Economic Theory, 2024 How to Cite?
Abstract

We introduce a learning model in which the decision maker does not know how recommendations are generated, called the contraction rule. We present behavioral postulates that characterize it. The contraction rule can be uniquely identified and reveals how the decision maker interprets and how much she trusts the recommendation. In a dynamic stationary setting, we show that the contraction rule is not dominated by completely following recommendations and is incompatible with a property called compliance with balanced recommendations. Following this negative result, we demonstrate that the contraction rule may generate and reinforce recency bias and disagreement.


Persistent Identifierhttp://hdl.handle.net/10722/344970
ISSN
2023 Impact Factor: 1.4
2023 SCImago Journal Rankings: 3.218

 

DC FieldValueLanguage
dc.contributor.authorKe, Shaowei-
dc.contributor.authorWu, Brian-
dc.contributor.authorZhao, Chen-
dc.date.accessioned2024-08-14T08:56:35Z-
dc.date.available2024-08-14T08:56:35Z-
dc.date.issued2024-08-08-
dc.identifier.citationJournal of Economic Theory, 2024-
dc.identifier.issn0022-0531-
dc.identifier.urihttp://hdl.handle.net/10722/344970-
dc.description.abstract<p>We introduce a learning model in which the decision maker does not know how recommendations are generated, called the contraction rule. We present behavioral postulates that characterize it. The contraction rule can be uniquely identified and reveals how the decision maker interprets and how much she trusts the recommendation. In a dynamic stationary setting, we show that the contraction rule is not dominated by completely following recommendations and is incompatible with a property called compliance with balanced recommendations. Following this negative result, we demonstrate that the contraction rule may generate and reinforce recency bias and disagreement.<br></p>-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofJournal of Economic Theory-
dc.titleLearning from a Black Box-
dc.typeArticle-
dc.identifier.doi10.1016/j.jet.2024.105886-
dc.identifier.eissn1095-7235-
dc.identifier.issnl0022-0531-

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