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Robin Hanson For Bayesian wannabes, are disagreements not about information? article Consider two agents who want to be Bayesians with a common prior, but who cannot due to computational limitations. If these agents agree that their estimates are consistent with certain easy-to-compute consistency constraints, then they can agree to disagree about any random variable only if they also agree to disagree, to a similar degree and in a stronger sense, about an average error. Yet average error is a state-independent random variable, and one agent’s estimate of it is also agreed to be state-independent. Thus suggests that disagreements are not fundamentally due to differing information about the state of the world.

For Bayesian wannabes, are disagreements not about information?

Robin Hanson

Theory and Decision, vol. 54, no. 2, 2003, pp. 105–123

Abstract

Consider two agents who want to be Bayesians with a common prior, but who cannot due to computational limitations. If these agents agree that their estimates are consistent with certain easy-to-compute consistency constraints, then they can agree to disagree about any random variable only if they also agree to disagree, to a similar degree and in a stronger sense, about an average error. Yet average error is a state-independent random variable, and one agent’s estimate of it is also agreed to be state-independent. Thus suggests that disagreements are not fundamentally due to differing information about the state of the world.

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