Learning from Private and Public Observation of Other's Actions
Manuel Amador and
Pierre-Olivier Weill ()
MPRA Paper from University Library of Munich, Germany
We study how a continuum of agents learn about disseminated information by observing others’ actions. Every period each agent observes a public and private noisy signal centered around the aggregate action taken by the population. The public signal represents an endogenous aggregate variable such as a price or a quantity. The private signal represents the information gathered through private communication and local interactions. We identify conditions such that the average learning curve is S-shaped: learning is slow initially, intensifies rapidly, and finally converges slowly to the truth. We show that increasing public information always slows down learning in the long run and, under some conditions, reduces welfare. Lastly, optimal diffusion of information requires that agents “strive to be different”: agents need to be rewarded for choosing actions away from the population average.
Keywords: Learning externality; welfare cost of public information (search for similar items in EconPapers)
JEL-codes: D80 D83 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:109
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