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

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 …

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 develop a new method for estimating industry-level and aggregate total factor
productivity (TFP) growth. Our method accounts for profits and adjustment costs, and uses …

Consumption-saving models with adjustment costs or discrete choices are typically hard to
solve numerically due to the presence of non-convexities. This paper provides a number of …

We introduce an envelope condition method (ECM) for solving dynamic programming
problems. The ECM method is simple to implement, dominates conventional value function …

Solving dynamic economic models that capture salient real-world heterogeneity and non-
linearity requires the approximation of high-dimensional functions. As their dimensionality …

This paper studies dynamic programming for quantile preference models, in which the agent
maximizes the stream of the future τ-quantile utilities, for τ∈(0, 1). We suggest numerical …

We study the reform of China's state-owned enterprises (SOE) with a focus on the
corporatization of SOEs. We first document the empirical patterns of the “grasp the large and …

We show how to use field-programmable gate arrays (FPGAs) and their associated
highlevel synthesis (HLS) compilers to solve heterogeneous agent models with incomplete …