Solution and Estimation Methods for DSGE Models

Abstract

This paper provides an overview of solution and estimation techniques for dynamic stochastic general equilibrium (DSGE) models. We cover the foundations of numerical approximation techniques as well as statistical inference and survey the latest developments in the field.

Keywords: approximation error analysis, Bayesian inference, DSGE model, frequentist inference, GMM estimation, impulse response function matching, likelihood-based inference, Metropolis-Hastings algorithm, minimum distance estimation, particle filter, perturbation methods, projection methods, sequential Monte Carlo

JEL Classification: C11, C13, C32, C52, C61, C63, E32, E52