Econometrica: Nov 2019, Volume 87, Issue 6
On the Efficiency of Social Learning
Dinah Rosenberg, Nicolas Vieille
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.
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Supplement to "On the Efficiency of Social Learning"
This file contains the proofs of the statements of "on the efficiency of online learning", with the exception of Theorem 2, which is proven in the main paper.