Sequential Learning under Informational Ambiguity

48 Pages Posted: 14 Nov 2019 Last revised: 7 Dec 2021

See all articles by Jaden Yang Chen

Jaden Yang Chen

Cornell University, Department of Economics

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

Chen, Jaden Yang, Sequential Learning under Informational Ambiguity (September 1, 2019). Available at SSRN: https://ssrn.com/abstract=3480231 or http://dx.doi.org/10.2139/ssrn.3480231

Jaden Yang Chen (Contact Author)

Cornell University, Department of Economics ( email )

Ithaca, NY
United States

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