Sequential Learning under Informational Ambiguity
48 Pages Posted: 14 Nov 2019 Last revised: 7 Dec 2021
Date Written: September 1, 2019
Abstract
This paper studies a sequential learning problem where individuals are ambiguous about other people's data-generating processes. This paper finds that the occurrence of an information cascade can be interpreted as a result of ambiguity instead of details of the true data-generating process as suggested by the literature. When there is sufficient ambiguity, for all possible data-generating processes, an information cascade occurs almost surely. This paper further shows that non-cascade may even represent a knife-edge case with respect to ambiguity. An arbitrarily small degree of ambiguity can produce a cascade when signals are bounded and destroy complete learning when signals are unbounded.
Keywords: Social learning, information cascades, ambiguity, herding
JEL Classification: D81, D83, C72
Suggested Citation: Suggested Citation