DSGE models have recently become one of the most frequently used tools in policy analysis. Nevertheless, their forecasting proprieties are still unexplored. In this article we address this problem by examining the quality of forecasts from a small size DSGE model, a trivariate VAR model and the...

This paper investigates the accuracy of point and density forecasts of four DSGE models for inflation, output growth and the federal funds rate. Model parameters are estimated and forecasts are derived successively from historical U.S. data vintages synchronized with the Fed's Greenbook...

This paper investigates the accuracy of forecasts from four DSGE models for inflation, output growth and the federal funds rate using a real-time dataset synchronized with the Fed’s Greenbook projections. Conditioning the model forecasts on the Greenbook nowcasts leads to forecasts that are as...

This paper investigates the accuracy of point and density forecasts of four DSGE models for inflation, output growth and the federal funds rate. Model parameters are estimated and forecasts are derived successively from historical US data vintages synchronized with the Fed's Greenbook...

The predictive likelihood is of particular relevance in a Bayesian setting when the purpose is to rank models in a forecast comparison exercise. This paper discusses how the predictive likelihood can be estimated for any subset of the observable variables in linear Gaussian state-space models...

We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets-Wouters model and its forecasts of real GDP growth and inflation are compared with those from two extensions. The first adds financial frictions and expands the observables to include a...

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...

The BoltzmannGibbs distribution is currently widely used in economic modeling. One of the applications is integrated with the DSGE (Dynamic Stochastic General Equilibrium) model. However, a question that arises concerns whether the BoltzmannGibbs distribution can be directly applied, without...

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...

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle...