The Reversible Jump Markov Chain Monte Carlo (RJMCMC) method can enhance Bayesian DSGE estimation by sampling from a posterior distribution spanning potentially nonnested models with parameter spaces of different dimensionality. We use the method to jointly sample from an ARMA process of unknown...

We relax the standard assumption in the dynamic stochastic general equilibrium (DSGE) literature that exogenous processes are governed by AR(1) processes and estimate ARMA (p,q) orders and parameters of exogenous processes. Methodologically, we contribute to the Bayesian DSGE literature by using...

We estimate a DSGE model where rare large shocks can occur, but replace the commonly used Gaussian assumption with a Student's t-distribution. Results from the Smets and Wouters (2007) model estimated on the usual set of macroeconomic time series over the 1964-2011 period indicate that 1) the...

We study the transmission of monetary shocks and monetary policy with a behavioral model, corrected for potential misspecification using the DSGE-VAR framework elaborated by DelNegro and Schorfheide (2004). In particular, we investigate if the central bank should react to movements in the...