This chapter provides an overview of solution and estimation techniques for dynamic
stochastic general equilibrium models. We cover the foundations of numerical …

Although almost nonexistent 15 years ago, there are now numerous papers that analyze
models with both aggregate uncertainty and a large number—typically a continuum—of …

We show how to enhance the performance of a Smolyak method for solving dynamic
economic models. First, we propose a more efficient implementation of the Smolyak method …

We introduce deep equilibrium nets (DEQNs)—a deep learning‐based method to compute
approximate functional rational expectations equilibria of economic models featuring a …

We develop numerically stable and accurate stochastic simulation approaches for solving
dynamic economic models. First, instead of standard least‐squares approximation methods …

We introduce a numerical algorithm for solving dynamic economic models that merges
stochastic simulation and projection approaches: we use simulation to approximate the …

An accurate global projection algorithm is critical for quantifying the basic moments of the
Diamond–Mortensen–Pissarides model. Log linearization understates the mean and …

We present a novel computational framework that can compute global solutions to high-
dimensional dynamic stochastic economic models on irregular state space geometries. This …

We survey numerical methods that are tractable in dynamic economic models with a finite,
large number of continuous state variables.(Examples of such models are new Keynesian …

We describe a sparse-grid collocation method to compute recursive solutions of dynamic
economies with a sizable number of state variables. We show how powerful this method can …