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...

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...

This paper finds the optimal consumption and asset allocation strategy for an Australian retiree who aims to maintain a level of minimum consumption. I use a discrete dynamic programming algorithm, with historical stock return distribution and a regime switching investment model, while taking...

I/B/E/S removes 6% of one-quarter-ahead earnings forecasts from the calculation of the consensus forecast. This study examines managers' role in these removals. We show optimistic forecasts are removed more often than pessimistic forecasts, after controlling for removal policies that I/B/E/S...

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 bring together the theories of duality and dynamic programming. We show that the dual of a separable dynamic optimization problem can be recursively decomposed. We provide a dual version of the principle of optimality and give conditions under which the dual Bellman operator is a contraction...

We study optimal contracts when R\&D is outsourced to another company. We find that, when a realistic assumption holds, the optimal contract always leads in equilibrium to the lowest acceptable chance of having a successful technical innovation, given announced compensations. This assumption is...

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...

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,...

We analyze optimal compensation schedules for the directors of two plants belonging to the same owner and producing the same good but serving geographically differentiated markets. Since the outcome of each director depends on his own effort and on a random variable representing market...