Knowing one's future preferences: A correlated agent model with Bayesian updating

We generalize two classes of statistical sequential incomplete information games: (1) those resembling typical signaling games, in which a single agent represents each player, allowing for information to be revealed about future play; and (2) those in which each player is represented by a set of independent agents, where moves do not reveal private information. The generalized model we develop, the Correlated Agent Model, relies on a parameter, ρ, which denotes the correlation between two agents' private information, i.e. the extent to which a player knows the future private component of her preferences. The independent agent and single agent models are special cases, where ρ=0 and ρ=1, respectively. The model also allows 0 < ρ < 1, a class of games which have not yet been considered. We apply the model to crisis bargaining and demonstrate how to estimate ρ, as well as parameters associated with utilities.