A new algorithm for the group minimization problem (GP) is proposed. The algorithm can be broadly described as follows. A suitable relaxation of(GP) is defined, in which any feasible point satisfies the group equation but may have negative components. The feasible points of the relaxation are...

We study the optimal pattern of outlays for a single firm pursuing an R&D program over time. In the deterministic case, (a) the amount of progress required to complete the project is known, and (b) the relationship between outlays and progress is known. In this case, it is optimal to increase...

This paper uses play-by-play accounts of virtually all regular season National Football League games for 1998-2000 to analyze teams' choices on fourth down between trying for a first down and kicking. Dynamic programming is used to estimate the values of possessing the ball at different points...

The goal of this paper is to study the problem of optimal dynamic policy formulation with competing political parties. We study a general class of problems, in which the two competing political parties have quadratic intertemporal objective functions, and in which the economy has a linear...

We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization. Quantum annealers attempt to solve an NP-hard problem by starting in a quantum superposition of all...

We study labor adjustment costs. We specify a dynamic optimization problem at the plant-level, allowing for both convex and non-convex adjustment costs. We estimate the parameters of the adjustment process using an indirect inference procedure in which simulated moments are matched with data...

This paper uses a dynamic optimization model to estimate the welfare gains that a small open economy can derive from insuring against natural disasters with catastrophe (CAT) bonds. We calibrate the model by reference to the risk of earthquakes, floods and storms in developing countries. We find...

This paper formulates a structural dynamic programming model of preschool investment choices of altruistic parents and then empirically estimates the structural parameters of the model using the NLSY79 data. The paper finds that preschool investment significantly boosts cognitive and...

We apply numerical dynamic programming to multi-asset dynamic portfolio optimization problems with proportional transaction costs. Examples include problems with one safe asset plus two to six risky stocks, and seven to 360 trading periods in a finite horizon problem. These examples show that it...