[UTMD-113] Social Learning with Correlated Information (by Yu Awaya, Vijay Krishna)

Yu Awaya, Vijay Krishna

We study a standard binary social learning model where agents’ information is serially correlated—it is generated by a Markov process. There is a unique equilibrium in which a herd, sometimes incorrect, always forms. In the long run, does greater persistence increase the likelihood that an incorrect herd forms? In the medium run (prior to the formation of a herd), does a greater similarity information—higher persistence—lead to a greater similarity of actions? The answer to both questions is no.