This paper estimates a monetary DSGE model with learning introduced from the primitive assumptions. The model nests infinite-horizon learning and features, such as habit formation in consumption and inflation indexation, that are essential for the model fit under rational expectations. I estimate the DSGE model by Bayesian methods, obtaining estimates of the main learning parameter, the constan...

In this paper, we develop and apply certain tools to evaluate the strengths and weaknesses of dynamic stochastic general equilibrium (DSGE) models. In particular, this paper makes three contributions: One, it argues the need for such tools to evaluate the usefulness of the these models; two, it defines these tools which take the form of prior and particularly posterior predictive analysis and p...

While DSGE models have been widely used by central banks for policy analysis, they seem to have been ineffective in calibrating the models for anticipating financial crises. To bring DSGE models closer to real situations, some of researchers have revised the traditional DSGE models. One of the modified DSGE models is the adaptive belief system model. In this framework, changes in sentiment can ...

Epstein-Zin preferences (or “EZ” preferences) have become increasingly popular in recent asset pricing work. Dynamic stochastic general equilibrium (DSGE) models which feature Epstein-Zin preferences are typically considered technically challenging, often thought to require sophisticated numerical solution methods to solve them and considerable additional thought to understand them. The purpose...

The primary objective of this paper is to revisit DSGE models with a view to appraise their statistical adequacy and propose ways to ameliorate their empirical pertinence. This paper brings out several weaknesses of the traditional DSGE modeling, including statistical misspecification, non-identification of deep parameters, substantive inadequacy, weak forecasting performance and potentially mi...

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...