American Economic Journal: Microeconomics
no. 1, February 2013
We study social learning by boundedly rational agents. Agents take
a decision in sequence, after observing their predecessors and a private signal. They are unable to make perfect inferences from their
predecessors' decisions: they only understand the relation between
the aggregate distribution of actions and the state of nature, and
make their inferences accordingly. We show that, in a discrete action
space, even if agents receive signals of unbounded precision, there
are asymptotic inefficiencies. In a continuous action space, compared
to the rational case, agents overweight early signals. Despite this behavioral bias, eventually agents learn the realized state of the
world and choose the correct action. (JEL D82, D83)
Guarino, Antonio, and Philippe Jehiel.
"Social Learning with Coarse Inference."
American Economic Journal: Microeconomics,
Asymmetric and Private Information; Mechanism Design
Search; Learning; Information and Knowledge; Communication; Belief