This paper studies disclosure games, allowing for large evidence spaces and general disclosure rules. A sender observes a piece of evidence about an unknown state and tries to influence the posterior belief of a receiver by disclosing evidence with possible omission . We focus on truth-leaning equilibria  , where the sender discloses truthfully when doing so is optimal, and the receiver does not discount off-path messages. We show that, given any disclosure rule, all equilibria are payoff equivalent and characterize the unique equilibrium valuefunction of the sender. We also propose a method to construct equilibria for a broad class of games. Applying these results, we study left-censored disclosure, where evidence is a sequence of signals, and the sender can truncate evidence from the left. In equilibrium, seemingly sub-optimal messages are disclosed, and the sender's disclosure contains the longest truncation that yields the maximal difference between the number of favorable and unfavorable signals .
We study a disclosure game with a large evidence space. There is an unknown binary state. A sender observes a sequence of binary signals about the state and discloses a left truncation of the sequence to a receiver in order to convince him that the state is good . We focus on truth-leaning equilibria (cf. Hart et al. (2017)) , where the sender discloses truthfully when doing so is optimal, and the receiver takes off-path disclosure at face value. In equilibrium, seemingly sub-optimal truncations are disclosed, and the disclosure contains the longest truncation that yields the maximal difference between the number of good and bad signals. We also study a general framework of disclosure games which is compatible with large evidence spaces, a wide range of disclosure technologies, and finitely many states. We characterize the unique equilibrium value function of the sender and propose a method to construct equilibria for a broad class of games .
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This paper studies disclosure games, allowing for large evidence spaces and general disclosure rules.
We study a disclosure game with a large evidence space. There is an unknown binary state.
R
piece of evidence about an unknown state and tries to influence the posterior belief of a receiver by disclosing evidence with possible omission
sequence of binary signals about the state and discloses a left truncation of the sequence to a receiver in order to convince him that the state is good
A
(cf. Hart et al. (2017))
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does not discount
takes
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messages. We show that, given any disclosure rule, all equilibria are payoff equivalent and characterize the unique equilibrium valuefunction of the sender. We also propose a method to construct equilibria for a broad class of games. Applying these results, we study left-censored disclosure, where evidence is a sequence of signals, and the sender can truncate evidence from the left.
disclosure at face value.
R
messages
truncations
D
sender's
R
favorable and unfavorable signals
good and bad signals. We also study a general framework of disclosure games which is compatible with large evidence spaces, a wide range of disclosure technologies, and finitely many states. We characterize the unique equilibrium value function of the sender and propose a method to construct equilibria for a broad class of games