An uninformed sender designs a mechanism that discloses information about her type to a privately informed receiver, who then decides whether to act. I impose a single-crossing assumption, so that the receiver with a higher type is more willing to act. Using a linear programming approach, I...

A budget-constrained buyer wants to purchase items from a shortlisted set. Items are differentiated by observable quality and sellers have private reserve prices for their items. The buyer's problem is to select a subset of maximal quality. Money does not enter the buyer's objective function,...

An uninformed sender designs a mechanism that discloses information about her type to a privately informed receiver, who then decides whether to act. I impose a single-crossing assumption, so that the receiver with a higher type is more willing to act. Using a linear programming approach, I...

We consider a “tenure-clock problem” in which a principal may set a deadline by which she needs to evaluate an agent's ability and decides whether to promote him or not. We embed this problem in a continuous-time model with both hidden action and hidden information, where the principal must...

We explore reinforcement learning methods for finding the optimal policy in the linear quadratic regulator (LQR) problem. In particular we consider the convergence of policy gradient methods in the setting of known and unknown parameters. We are able to produce a global linear convergence...

I examine how the communication incentive of an agent (sender) changes when the prior of the principal (receiver) about the agent's private information becomes more optimistic (in the sense of monotone likelihood ratio dominance). I use the canonical model of strategic communication (Crawford...

We provide a technique for constructing optimal multiattribute screening contracts in a general setting with one-dimensional types based on necessary optimality conditions. Our approach allows for type-dependent participation constraints and arbitrary risk profiles. As an example we discuss...