We study a generalization of the classical monopoly insurance problem under adverse selection where we allow for a random distribution of losses, possibly correlated with the agent's risk parameter that is private information. Our main purpose is to provide a convenient analytic model that...

We study information design with multiple privately informed agents who interact in a game. Each agent's utility is linear in a real-valued state. We show that there always exists an optimal mechanism that is laminar partitional and bound its “complexity.” For each type profile, such a...

We study a generalization of the classical monopoly insurance problem under adverse selection (see Stiglitz [1977]) where we allow for a random distribution of losses, possibly correlated with the agent’s risk parameter that is private information. Our model explains patterns of observed...

A signal is privacy-preserving with respect to a collection of privacy sets, if the posterior probability assigned to every privacy set remains unchanged conditional on any signal realization. We characterize the privacy-preserving signals for arbitrary state space and arbitrary privacy sets. A...

We use the tools of mechanism design, combined with the theory of risk measures, to analyze a model where a cash constrained owner of an asset with stochastic returns raises capital from a population of investors that di¤er in their risk aversion and budget constraints. The distribution of the...