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On the Efficiency of Social Learning
Author(s) -
Rosenberg Dinah,
Vieille Nicolas
Publication year - 2019
Publication title -
econometrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.7
H-Index - 199
eISSN - 1468-0262
pISSN - 0012-9682
DOI - 10.3982/ecta15845
Subject(s) - sequence (biology) , simple (philosophy) , basis (linear algebra) , social learning , private information retrieval , distribution (mathematics) , binary number , signal (programming language) , welfare , artificial intelligence , econometrics , computer science , microeconomics , economics , mathematics , statistics , arithmetic , knowledge management , mathematical analysis , philosophy , genetics , geometry , epistemology , market economy , biology , programming language
We revisit prominent learning models in which a sequence of agents make a binary decision on the basis of both a private signal and information related to past choices. We analyze the efficiency of learning in these models, measured in terms of the expected welfare. We show that, irrespective of the distribution of private signals, learning efficiency is the same whether each agent observes the entire sequence of earlier decisions or only the previous decision. In addition, we provide a simple condition on the signal distributions that is necessary and sufficient for learning efficiency. This condition fails to hold in many cases of interest. We discuss a number of extensions and variants.