Dynamic discrete choice (DDC) models are not identified nonparametrically, but the non-identification of models does not necessarily imply the nonidentification of counterfactuals. We derive novel results for the identification of counterfactuals in DDC models, such as non-additive changes in...

We show how to use field-programmable gate arrays (FPGAs) and their associated high-level synthesis (HLS) compilers to solve heterogeneous agent models with incomplete markets and aggregate uncertainty (Krusell and Smith (1998)). We document that the acceleration delivered by one single FPGA is...

With capital-skill complementarity, the secular decline in the price of capital equipment due to equipment-specific technological progress (ESTP) keeps pushing up the demand for skilled relative to unskilled labor and raising the skill premium. This paper quantitatively characterizes the...

We introduce a novel simulated certainty equivalent approximation (SCEQ) method for solving dynamic stochastic problems. Our examples show that SCEQ can quickly solve high-dimensional finite- or infinite-horizon, stationary or non- stationary dynamic stochastic problems with hundreds of state...

This paper introduces a nonlinear certainty-equivalent approximation method for dynamic stochastic problems. We first introduce a novel, stable, and efficient method for computing the decision rules in deterministic dynamic economic problems. We use the results as nonlinear and global...

We introduce a computational technique- precomputation of integrals - that makes it possible to construct conditional expectation functions in dynamic stochastic models in the initial stage of a solution procedure. This technique is very general: it works for a broad class of approximating...

A divide and conquer algorithm for exploiting policy function monotonicity is proposed and analyzed. To solve a discrete problem with n states and n choices, the algorithm requires at most nlog2(n)+5n objective function evaluations. In contrast, existing methods for nonconcave problems require...

This paper develops and estimates a model of college basketball teams' search for scoring opportunities, to provide a benchmark of the winning margin distributions that should arise if teams' only goal is to win. I estimate the model's structural parameters using first-half play-by-play data...

Morton and Wecker (1977) stated that the value iteration algorithm solves a dynamic program's policy function faster than its value function when the limiting Markov chain is ergodic. I show that their proof is incomplete, and provide a new proof of this classic result. I use this result to...

Single-agent dynamic discrete choice models are typically estimated using heavily parametrized econometric frameworks, making them susceptible to model misspecification. This paper investigates how misspecification affects the results of inference in these models. Specifically, we consider a...