One of the leading methods of estimating the structural parameters of DSGE models is the VAR-based impulse response … sheds new light on the choice of the weighting matrix and covers both weakly and strongly identified DSGE model parameters …

One of the leading methods of estimating the structural parameters of DSGE models is the VAR-based impulse response … both weakly and strongly identified DSGE model parameters. We also show that under our assumptions special care is needed …

One of the leading methods of estimating the structural parameters of DSGE models is the VAR-based impulse response … sheds new light on the choice of the weighting matrix and covers both weakly and strongly identified DSGE model parameters …

large-scale SSMs, making it particularly useful to estimate dynamic stochastic general equilibrium (DSGE) models and dynamic … factor models. Tests using a medium-scale DSGE model, namely the 2007 version of the Smets and Wouters model, show that the …

stability of the solutions of linear dynamic stochastic general equilibrium (DSGE) models. Comparing seven different solution … inaccuracies. The analysis is then performed for a database of roughly 100 DSGE models from the literature and a large set of draws …

solution methods suitable for standard DSGE estimation and analysis procedures. This approach generalizes the time …

methodology of constructing Dynamic Stochastic General Equilibrium (DSGE) consistent prior distributions for Bayesian Vector … Ravenna (2007) regarding structural VAR (SVAR) models and the normal prior density of the DSGE parameter vector. In line with … used to rank competing DSGE theories that aim to explain the same observed data (Geweke, 2005). Finally, motivated by the …

We test the standard New Keynesian (NK) Dynamic Stochastic General Equilibrium (DSGE) model under the condition with …. Overall, our findings provide important implications on the modelling of expectation formation in the DSGE framework. …

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 … maximize the marginal likelihood of the Bayesian VAR provides a method for isolating subsets of DSGE parameter priors that are …