We propose a new method for solving high-dimensional dynamic programming problems and recursive competitive equilibria with a large (but finite) number of heterogeneous agents using deep learning. The "curse of dimensionality" is avoided due to four complementary techniques: (1) exploiting...

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...

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...

We study the inferences about labor adjustment costs obtained by the 'gap methodology' of Caballero and Engel [1993] and Caballero, Engel and Haltiwanger [1997]. In that approach, the policy function of a manufacturing plant is assumed to depend on the gap between a target and the current level...

The new open-economy macroeconomics' seeks to provide an improved basis for monetary and exchange-rate policy through the construction of open-economy models that feature rational expectations, optimizing agents, and slowly adjusting prices of goods. This paper promotes an alternative approach...

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...

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...