HEC Research Papers Series,
HEC Paris

Abstract: We revisit well-known models of learning in which a sequence of agents make a binary decision on the basis of a private signal and additional information. We introduce efficiency measures, aimed at capturing the speed of learning in such contexts. Whatever the distribution of private signals, we show that the learning efficiency is the same, whether each agent observes the entire sequence of earlier decisions, or only the previous decision. We provide a simple necessary and sufficient condition on the signal distributions under which learning is efficient. This condition fails to hold in many prominent cases of interest. Extensions are discussed.

Keywords: Social Learning

JEL-codes: D83

41 pages, November 9, 2017

Note: models of learning; Social Learning

Full text files

papers.cfm?abstract_id=3081876  Full text

Download statistics

• HEC Paris
• Ordering Working Papers
• Home page for this series

Questions (including download problems) about the papers in this series should be directed to Antoine Haldemann ()
Report other problems with accessing this service to Sune Karlsson ().

RePEc:ebg:heccah:1246This page generated on 2024-09-13 22:19:53.