We show that a solution to the problem of mechanism selection by an informed principal exists in a large class of environments with “generalized private values”: the agents’ payoff functions are independent of the principal’s type. The solution is an extension of Maskin and Tirole’s...

We present a common value mechanism design model for an informed principal where only the principal has private information, but her one-dimensional private information is allowed to be distributed according to any probability measure. For this model we characterize the set of pure-strategy...

We consider the situation where the owner of some good wants to sell the good to one of several potential buyers. We assume that the owner possesses private information about the buyers' valuations of the good, and analyze this model as an informed principal mechanism design model. In an...

We consider the problem of mechanism design by a principal who has private information. We point out a simple condition under which the privacy of the principal's information is irrelevant in the sense that the mechanism implemented by the principal coincides with the mechanism that would be...

We show that, in environments with independent private values and transferable utility, a privately informed principal can solve her mechanism selection problem by implementing an allocation that is ex-ante optimal for her. No type of the principal can gain from proposing an alternative...

We study the informed-principal problem in a bilateral asymmetric information trading setting with interdependent values and quasi-linear utilities. The informed seller proposes a mechanism and voluntarily certifies information about the good's characteristics. When the set of certifiable...

We rationalize a special type of sharing information which can typically be found in markets for occupational disability insurances. There, firms share information about acceptances and rejections of an applicant. We set up a multiple-step signalling model with uninformed agents and endogenize...