Predicting information from Choice

An analyst observes the frequency with which an agent takes actions, but not the frequency with which she takes actions conditional on a payoff relevant state. In this setting, we ask when the analyst can rationalize the agent’s choices as the outcome of the agent learning something about the state before taking action. Our characterization marries the obedience approach in information de- sign (Bergemann and Morris, 2016) and the belief approach in Bayesian persuasion (Kamenica and Gentzkow, 2011) relying on a theorem by Strassen (1965) and Hall’s marriage theorem. We apply our results to ring-network games and to identify conditions under which a data set is consistent with a public information structure in first-order Bayesian persuasion games.