Conversation, Observational Learning, and Informational Cascades

H. Henry Cao and David Hirshleifer
Abstract
We offer a model to explain why groups of people sometimes converge upon poor decisions
and are prone to fads, even though they can discuss the outcomes of their choices.
Models of informational herding or cascades have examined how rational individuals learn
by observing predecessors’ actions, and show that when individuals stop using their own private
signals, improvements in decision quality cease. A literature on word-of-mouth learning
shows how observation of outcomes as well as actions can cause convergence upon correct
decisions. However, the assumptions of these models differ considerably from those of the
cascades/herding literature. In a setting which adds ‘conversational’ learning about both
the payoff outcomes of predecessors to a basic cascades model, we describe conditions under
which (1) cascades/herding occurs with probability one; (2) once started there is a positive
probability (generally less than one) that a cascade lasts forever; (3) cascades aggregate
information inefficiently and are fragile; (4) the ability to observe past payoffs can reduce
average decision accuracy and welfare; and (5) delay in observation of payoffs can improve
average accuracy and welfare.
Created:Sun, 24 Oct 2004 11:32:19 GMT


Original: http://jondron.net/cofind/frshowresource.php?tid=5303&resid=543
Posted: October 24, 2004, 5:32 am

I am a professional learner, employed as a Full Professor at Athabasca University, where I research lots of things broadly in the area of learning and technology and teach mainly in the School of Computing & Information Systems, of which I am the Chair. I am married, with two grown-up children, and live in beautiful Vancouver.

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