Conversation, Observational Learning, and Informational Cascades
H. Henry Cao
University of North Carolina (UNC) at Chapel Hill - Finance Area
David A. Hirshleifer
University of California, Irvine - Paul Merage School of Business
November 13, 2000
Dice Center Working Paper No. 2001-5
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.
This version of the paper is superseded by "Taking the Road Less Traveled by: Does Conversation Eradicate Pernicious Cascades?," Cao, H. Henry, Han, Bing and Hirshleifer, David A., http://ssrn.com/abstract=422180
Number of Pages in PDF File: 37
JEL Classification: D82, D83, D7, D00, G14working papers series
Date posted: May 9, 2001 ; Last revised: August 20, 2009
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