This paper is intended to be pedagogical rather than a presentation of original research. We describe a simple dynamic, stochastic general equilibrium (DSGE) model with capital utilization, capital adjustment costs, and a simple Cobb-Douglas technology to illustrate how DSGE models can be used to explain the past and to forecast the future. We identify one method to directly estimate latent var...

Advanced Bayesian methods are employed in estimating dynamic stochastic general equilibrium (DSGE) models. Although policymakers and practitioners are particularly interested in DSGE models, these are typically too stylized to be taken directly to the data and often yield weak prediction results. Hybrid models can deal with some of the DSGE model misspeci…cations. Major advances in Bayesian est...

The presence of stochastic and deterministic trends in DSGE models may imply that the values of the agents’objective functions are in…nite. For the households’, this might happen if the consumption process has a su¢ ciently high growth rate and the subjective discount factor is very close to 1. The problem associated with objective functions attaining in…nite values is that they do not have an ...

Bayesian estimation of DSGE models typically uses Markov chain Monte Carlo as importance sampling (IS) algorithms have a difficult time in high-dimensional spaces. I develop improved IS algorithms for DSGE models using recent advances in Monte Carlo methods known as sequential Monte Carlo samplers. Sequential Monte Carlo samplers are a generalization of particle filtering designed for full simu...

In this paper we treat the issue of forecasting with DSGE and DSGE-VAR models, with particular attention to Bayesian estimation of the predictive distribution and its mean and covariance. As a novel contribution to the forecasting literature, which extends beyond (log-linearized) DSGE models and DSGE-VARs, we show how the value of the h-step-ahead marginal and joint predictive likelihood for a ...

This paper deals with Dynamic Stochastic General Equilibrium (DSGE) models under a multivariate student-t distribution for the structural shocks. Based on the solution algorithm of Klein (2000) and the gamma-normal representation of the t -distribution, the TaRB-MH algorithm of Chib and Ramamurthy (2010) is used to estimate the model. A technique for estimating the marginal likelihood of the DS...

Standard practice for the estimation of dynamic stochastic general equilibrium (DSGE) models maintains the assumption that economic variables are properly measured by a single indicator, and that all relevant information for the estimation is summarized by a small number of data series. However, recent empirical research on factor models has shown that information contained in large data sets i...

Standard practice for the estimation of dynamic stochastic general equilibrium (DSGE) models maintains the assumption that economic variables are properly measured by a single indicator, and that all relevant information for the estimation is summarized by a small number of data series. However, recent empirical research on factor models has shown that information contained in large data sets i...

This Paper describes a procedure for constructing theory restricted prior distributions for BVAR models. The Bayes Factor, which is obtained without any additional computational effort, can be used to assess the plausibility of the restrictions imposed on the VAR parameter vector by competing DSGE models. In other words, it is possible to rank the amount of abstraction implied by each DSGE mode...