This paper presents a framework for empirical analysis of dynamic macroeconomic models using Bayesian filtering, with a specific focus on the state-space formulation of New Keynesian Dynamic Stochastic General Equilibrium (NK DSGE) models with multiple regimes. We outline the theoretical...

We estimate a regime-switching DSGE model with a banking sector to explain incomplete and asymmetric interest rate pass-through, especially in the presence of a binding zero lower bound (ZLB) constraint. The model is estimated using Bayesian techniques on US data between 1985 and 2016. The...

Rational expectations (RE) has been dominant both in the economic literature and in the macromodels routinely used in central banks. The RE assumption has recently come under attack as one of the drawbacks of the Dynamic Stochastic General Equilibrium (DSGE modeling) paradigm. This study...

We analyse the implications of asymmetric monetary policy rules by estimating Markovswitching DSGE models for the euro area (EA) and the US. The estimations show that until mid-2014 the ECB's response to inflation was more forceful when inflation was above 2% than below 2%. Since then, the ECB's...

We analyse the implications of asymmetric monetary policy rules by estimating Markovswitching DSGE models for the euro area (EA) and the US. The estimations show that until mid-2014 the ECB's response to in ation was more forceful when in ation was above 2% than below 2%. Since then, the ECB's...

The time-varying natural rate of interest and output and the implied medium term inflation target for the US economy are estimated over the period 1983-2005. The estimation is conducted within the New-Keynesian framework using Bayesian and Kalman-filter estimation techniques. With the...

We estimate a small open-economy DSGE model for Norway with two specifications of monetary policy: a simple instrument rule and optimal policy based on an intertemporal loss function. The empirical fit of the model with optimal policy is as good as the model with a simple rule. This result is...

New-generation DSGE models are sometimes misspecified in dimensions that matter for their forecasting performance. The paper suggests one way to improve the forecasts of a DSGE model using a conditioning information that need not be accurate. The technique presented allows for agents to...