Monotone persuasion

We explore Bayesian persuasion environments in which the state and action spaces are ordered, allowing for complementarity between actions and types. Building on the literature on monotone comparative statics, we identify conditions that guarantee that these are optimal among all (possibly non-monotone) signal structures. When the action space is binary, supermodularity of the sender's and receiver's preferences suffices for the optimal signal to have a monotone structure. With a continuum of actions, the conditions are more intriguing. We identify a novel single-crossing condition using a virtual utility representation of the sender's payoff. We also provide a technique to compute the optimal monotone signal structure, even when this monotonicity is due to an exogenous constraint. Applications are given to quadratic loss functions with biases, capacity constraints, and credit ratings.