Common Learning

Martin William Cripps, Jeffrey Ely, George J. Mailath () and Larry Samuelson
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Larry Samuelson: University of Wisconsin

No 1575, Cowles Foundation Discussion Papers from Cowles Foundation, Yale University

Abstract: Consider two agents who learn the value of an unknown parameter by observing a sequence of private signals. The signals are independent and identically distributed across time but not necessarily agents. Does it follow that the agents will commonly learn its value, i.e., that the true value of the parameter will become (approximate) common-knowledge? We show that the answer is affirmative when each agent's signal space is finite and show by example that common learning can fail when observations come from a countably infinite signal space.

Keywords: Common learning; Common belief; Private signals; Private beliefs (search for similar items in EconPapers)
JEL-codes: D82 D83 (search for similar items in EconPapers)
Date: 2006-08
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Published in Econometrics (2008), 76(4): 909-933

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http://cowles.econ.yale.edu/P/cd/d15b/d1575.pdf (application/pdf)

Related works:
Working Paper: Common Learning (2006)
Working Paper: Common Learning (2007)
Working Paper: Common Learning (2007)
Journal Article: Common Learning (2008)
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