Common learning with intertemporal dependence
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.
KeywordsCommon learning Common belief Private signals Private beliefs
JEL ClassificationD82 D83
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- Billingsley P (1979) Probability and measure, 1st edn. Wiley, New YorkGoogle Scholar
- Brémaud P (1999) Markov chains: Gibbs fields, Monte Carlo simulation, and queues. Springer, New YorkGoogle Scholar
- den Hollander F (2000) Large deviations. American Mathematical Society, ProvidenceGoogle Scholar
- Rubinstein A (1989) The electronic mail game: Strategic behavior under almost common knowledge. Am Econ Rev 79(3): 385–391Google Scholar