Common Priors and Markov Chains
AbstractThe type function of an agent, in a type space, associates with each state a probability distribution on the type space. Thus, a type function can be considered as a Markov chain on the state space. A common prior for the space turns out to be a probability distribution which is invariant under the type functions of all agents. Using the Markovian structure of type spaces we show that a necessary and sufficient condition for the existence of a common prior is that for each random variable it is common knowledge that all its joint averagings converge to the same value.
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Bibliographic InfoPaper provided by EconWPA in its series Game Theory and Information with number 9610008.
Length: 8 pages
Date of creation: 21 Oct 1996
Date of revision:
Note: Type of Document - postscript; prepared on unix; pages: 8
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Type spaces; prior; common prior; Markov chain;
Find related papers by JEL classification:
- C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
- D8 - Microeconomics - - Information, Knowledge, and Uncertainty
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