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 across agents. We show that when each agent's signal space is finite, the agents will commonly learn the value of the parameter, that is, that the true value of the parameter will become approximate common knowledge. The essential step in this argument is to express the expectation of one agent's signals, conditional on those of the other agent, in terms of a Markov chain. This allows us to invoke a contraction mapping principle ensuring that if one agent's signals are close to those expected under a particular value of the parameter, then that agent expects the other agent's signals to be even closer to those expected under the parameter value. In contrast, if the agents' observations come from a countably infinite signal space, then this contraction mapping property fails. We show by example that common learning can fail in this case. Copyright Copyright 2008 by The Econometric Society.
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Paper
Martin W. Cripps & Jeffrey C. Ely & George J. Mailath & Larry Samuelson, 2006.
"Common Learning,"
Levine's Bibliography
321307000000000355, UCLA Department of Economics.
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Martin W. Cripps & Jeffrey C. Ely & George J. Mailath & Larry Samuelson, 2006.
"Common Learning,"
Cowles Foundation Discussion Papers
1575R, Cowles Foundation, Yale University, revised Jun 2007.
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Martin W. Cripps & Jeffrey C. Ely & George J. Mailath & Larry Samuelson, 2007.
"Common Learning,"
PIER Working Paper Archive
07-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Carlsson, Hans & van Damme, Eric, 1993.
"Global Games and Equilibrium Selection,"
Econometrica,
Econometric Society, vol. 61(5), pages 989-1018, September.
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