This paper reviews Bayesian methods that have been developed in recent years to estimate
and evaluate dynamic stochastic general equilibrium (DSGE) models. We consider the …

Bayesian forecasting is a natural product of a Bayesian approach to inference. The
Bayesian approach in general requires explicit formulation of a model, and conditioning on …

Using a Bayesian likelihood approach, we estimate a dynamic stochastic general
equilibrium model for the US economy using seven macroeconomic time series. The model …

This paper develops and estimates a dynamic stochastic general equilibrium (DSGE) model
with sticky prices and wages for the euro area. The model incorporates various other …

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

In this course we perform an introduction to Bayesian methods, we show some basic
definitions and properties of the bayesian approach. We have taken the content from the …

The last twenty years have witnessed tremendous advances in the mathematical, statistical,
and computational tools available to applied macroeconomists. This rapidly evolving field …

Dynamic stochastic general equilibrium (DSGE) models use modern macroeconomic theory
to explain and predict comovements of aggregate time series over the business cycle and to …

In this paper we propose a Bayesian econometric procedure for the evaluation and
comparison of DSGE models. Unlike in many previous econometric approaches we …

This paper shows how particle filtering facilitates likelihood-based inference in dynamic
macroeconomic models. The economies can be non-linear and/or non-normal. We describe …