vector can be recovered from the BVAR posterior estimates: a new 'quasi-Bayesian' DSGE estimation. An empirical application … stochastic general equilibrium (DSGE) model. We use the DSGE model priors to determine the moments of an independent Normal …-Wishart prior for the VAR parameters. Two hyper-parameters control the tightness of the DSGE-implied priors on the autoregressive …

methodology of constructing Dynamic Stochastic General Equilibrium (DSGE) consistent prior distributions for Bayesian Vector … Autoregressive (BVAR) models. The moments of the assumed Normal-Inverse Wishart (no conjugate) prior distribution of the VAR … Ravenna (2007) regarding structural VAR (SVAR) models and the normal prior density of the DSGE parameter vector. In line with …

misspecification using the DSGE-VAR framework elaborated by DelNegro and Schorfheide (2004). In particular, we investigate if the …

This Paper describes a procedure for constructing theory restricted prior distributions for BVAR models. The Bayes … 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 model from the historical data. …

Over the past 10 years dynamic stochastic general equilibrium (DSGE) models have become an important tool in … quantitative macroeconomics. However, DSGE models were not considered as a forecasting tool until very recently. The objective of … this paper is twofold. First, we compare the forecasting ability of a canonical DSGE model for the Spanish economy with …

-time forecasts from a richly-specified DSGE model to those from the Survey of Professional Forecasters, Bayesian VARs and VARs using … priors from a DSGE model. We show that the analyzed DSGE model is relatively successful in forecasting the US economy in the … BVARs and DSGE-VARs. Compared to the SPF, the DSGE model generates better output forecasts at longer horizons, but less …

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus … BVAR can outperform the NAWM. …

Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are … on a widely-used DSGE model to investigate the power of these tests. We find that in specification testing they have weak … power relative to an in-sample indirect inference test; this implies that a DSGE model may be badly mis-specified and still …

contains relevant information for inflation in some model classes. Money-based New Keynesian DSGE models and VARs incorporating …