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Reny. University of Chicago", "event_subtitle":"Philip J. Reny. University of Chicago", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"\u201cNatural Language Equilibrium I\u201d studies the effect of a commonly understood language on signaling game equilibria under the convention that off-path statements are interpreted as true unless they can be seen as a rational attempt to deceive. With this convention it was shown that, generically, only stable equilibrium outcomes of the setting with language can arise. Here, we strengthen the convention by also requiring that any statement must be interpreted as true according to its literal meaning unless doing so would make it profitable to use the statement deceptively. 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Using contemporary survey data from 2010, we nevertheless find that detectable traces remain: residents in historically exposed prefectures express stronger support for the right to discuss public affairs and for limiting government involvement in private affairs. 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Unlike in standard persuasion models, the information seller (IS) is not affected by actions taken by the information buyer (IB), and is concerned solely with maximizing the revenue from selling information to the IB. Offering some information for free may increase the IB\u2019s willingness to pay for additional information. The information that the IB seeks is modeled as information about the state of the world. Initially, the IB only knows the prior distribution over possible state. The IS supplies both free and paid information through signals whose state\u2011dependent distributions determine the IB\u2019s posterior via Bayes\u2019 rule. The IB\u2019s utility is a function of the posterior. An optimal free signal is one that maximizes the IS\u2019s expected revenue from the subsequent paid signal. That revenue is equal to the IB\u2019s expected gain in utility from the posterior induced by the free signal to the one induced by the paid signal. The paper characterizes the optimal free and paid signals and derives a formula for the maximal revenue in terms of the IB\u2019s utility function. It shows that any revenue gain for the IS from providing free information is accompanied by an equally large or larger direct loss to the IB, implying that free information is never socially beneficial. Whether or not free information can increase the IS\u2019s revenue depends on the form of the IB\u2019s utility function. In the two-state case, the utility functions that allow such gains are fully characterized. In the general case, only necessary conditions are obtained. In particular, if the IB\u2019s utility function is convex, the IS can never profit from providing free information. This occurs, for example, when the IB uses the information to solve a decision problem. By contrast, when the IB is engaged in strategic interaction with a third party, the IS may benefit from providing free information. 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