We develop a result on Bayesian updating , dubbed information validates the prior (IVP). Roughly, when two agents have different priors, each believes that a (Blackwell) more informative experiment will, on average, bring the other 's posterior mean closer to his own prior mean. We apply the result in two contexts of games of asymmetric information: voluntary testing or certification, and costly signaling or falsification. IVP can be used to determine how an agent's behavior responds to additional exogenous or endogenous information. We discuss economic implications.
We develop a result on expected posteriors for Bayesians with heterogenous priors , dubbed information validates the prior (IVP). Under familiar ordering requirements, Anne expects a (Blackwell) more informative experiment to bring Bob 's posterior mean closer to Anne's prior mean. We apply the result in two contexts of games of asymmetric information: voluntary testing or certification, and costly signaling or falsification. IVP can be used to determine how an agent's behavior responds to additional exogenous or endogenous information. We discuss economic implications.
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Bayesian updating
expected posteriors for Bayesians with heterogenous priors
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Roughly, when two agents have different priors, each believes that
Under familiar ordering requirements, Anne expects
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will, on average, bring the other
to bring Bob
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his own
Anne's