We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call Dynamic Pools, and use it to investigate the relative forecasting performance of DSGE models with and without financial frictions for output growth and inflation from 1992 to 2011. We...

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call dynamic pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, for output...

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call Dynamic Pools, and use it to investigate the relative forecasting performance of DSGE models with and without financial frictions for output growth and inflation from 1992 to 2011. We...

This paper uses a modified version of the DSGE model estimated in Smets and Wouters (2003) to generate a prior distribution for a vector autoregression, following the approach in Del Negro and Schorfheide (2003). This DSGE-VAR is fitted to Euro area data on GDP, consumption, investment, nominal...

This paper uses a modified version of the DSGE model estimated in Smets and Wouters (2003) to generate a prior distribution for a vector autoregression, following the approach in Del Negro and Schorfheide (2003). This DSGE-VAR is fitted to Euro area data on GDP, consumption, investment, nominal...

This paper develops and illustrates a simple method to generate a DSGE model-based forecast for variables that do not explicitly appear in the model (non-core variables). We use auxiliary regressions that resemble measurement equations in a dynamic factor model to link the non-core variables to...

The Paper provides new tools for the evaluation of DSGE models, and applies it to a large-scale New Keynesian dynamic stochastic general equilibrium (DSGE) model with price and wage stickiness and capital accumulation. Specifically, we approximate the DSGE model by a vector autoregression (VAR),...

German business cycle forecasts refer to the whole country. However, the usefulness of these forecasts at the regional level is not uncontroversial. Significant deviations between regional and national forecasts could occur if the sectoral structure is different. In this case, the forecast for...

This paper develops and applies tools to assess multivariate aspects of Bayesian Dynamic Stochastic General Equilibrium (DSGE) model forecasts and their ability to predict comovements among key macroeconomic variables. We construct posterior predictive checks to evaluate conditional and...

This paper develops a vector autoregression (VAR) for time series which are observed at mixed frequencies - quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to...