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In this paper, I review the literature on the formulation and estimation of
dynamic stochastic general equilibrium (DSGE) models with a special emphasis on
Bayesian methods. First, I discuss the evolution of DSGE models over the last couple
of decades. Second, I explain why the profession has decided to estimate these models
using Bayesian methods. Third, I briefly introduce some of the techniques required
to compute and estimate these models. Fourth, I illustrate the techniques under consideration
by estimating a benchmark DSGE model with real and nominal rigidities.
I conclude by offering some pointers for future research.
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