Common learning with intertemporal dependence

Martin W. Cripps; Jeffrey C. Ely; George J. Mailath; Larry Samuelson

doi:10.1007/s00182-011-0313-7

Common learning with intertemporal dependence

Martin W. Cripps, Jeffrey C. Ely, George J. Mailath, Larry Samuelson

Economics

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Consider two agents who learn the value of an unknown parameter by observing a sequence of private signals. Will the agents commonly learn the value of the parameter, i. e., will the true value of the parameter become approximate common-knowledge? If the signals are independent and identically distributed across time (but not necessarily across agents), the answer is yes (Cripps et al., Econometrica, 76(4):909-933, 2008). This paper explores the implications of allowing the signals to be dependent over time. We present a counterexample showing that even extremely simple time dependence can preclude common learning, and present sufficient conditions for common learning.

Original language	English (US)
Pages (from-to)	55-98
Number of pages	44
Journal	International Journal of Game Theory
Volume	42
Issue number	1
DOIs	https://doi.org/10.1007/s00182-011-0313-7
State	Published - Jan 1 2013

Keywords

Common belief
Common learning
Private beliefs
Private signals

ASJC Scopus subject areas

Statistics and Probability
Mathematics (miscellaneous)
Social Sciences (miscellaneous)
Economics and Econometrics
Statistics, Probability and Uncertainty

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