Matching Theory and Data: Bayesian Vector Autoregression and Dynamic Stochastic General Equilibrium Models
Title: Matching Theory and Data: Bayesian Vector Autoregression and Dynamic Stochastic General Equilibrium Models
Author: KRIWOLUZKY, Alexander
Series/Report no.: EUI MWP; 2009/27
This paper shows how to identify the structural shocks of a Vector Autoregression (VAR) while simultaneously estimating a dynamic stochastic general equilibrium (DSGE) model that is not assumed to replicate the data-generating process. It proposes a framework for estimating the parameters of the VAR model and the DSGE model jointly: the VAR model is identified by sign restrictions derived from the DSGE model; the DSGE model is estimated by matching the corresponding impulse response functions.
Subject: Bayesian Model Estimation; Vector Autoregression; Identification; C51
I am especially thankful to Harald Uhlig, Chris Sims, Bartosz Mackowiak, Helmut Lütkepohl, Wouter den Haan, Francesco Ravazzolo, Lenno Uusküla, Morten Ravn and Martin Kliem for their comments and suggestions. The paper further benefitted from seminar participants at Norges Bank.
Type of Access: openAccess