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 ECO; 2009/29
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
Type of Access: openAccess