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Common LearningMartin CrippsUniversity College London - Department of Economics; Washington University in Saint Louis - John M. Olin Business School J.C. ElyNorthwestern University - Department of Economics George J. MailathUniversity of Pennsylvania - Department of Economics Larry SamuelsonYale University June 20, 2007 Cowles Foundation Discussion Paper No. 1575R PIER Working Paper No. 07-018 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 across agents. We show that that when each agent's signal space is finite, the agents will commonly learn its value, i.e., that the true value of the parameter will become approximate common-knowledge. 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.
Number of Pages in PDF File: 38 Keywords: Common learning, Common belief, Private signals, Private beliefs JEL Classification: D82, D83 working papers seriesDate posted: June 21, 2007Suggested CitationContact Information
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