This thesis makes three main contributions to the literature on Dynamic Stochastic General Equilibrium (DSGE) models in Macroeconomics. As no previous studies have studied the Chinese economy from the perspective of DSGE, the first contribution of this thesis is estimating a DSGE model for China through a Bayesian approach using the Chinese quarterly post-economic reform data representing the m...

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 ...

DSGE models are designed to mimic only certain aspects of reality, usually speci…ed moments of observable data. They typically have other implications that are clearly false and lead to their immediate rejection if taken literally. Widely used calibration exercises compare the implications of DSGE models for the distribution of speci…ed sample moments with the corresponding data. This paper sho...

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...

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...

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...

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-steps ahead forecasts. In the empirical analysis, we examine the forecasting performance of the New Area-Wide Model (NAWM) that has been designed f...

In this paper, we investigate the consequences of breaks in mean for the estimates of model parameters and the resulting inferences about the structure of the economy and policy implications. We explore the behavior of DSGE models that undergo occasional, but permanent shocks to the parameters that determine their steady state. We present a method for approximating the state space representatio...

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...