Matching Theory and Data: Bayesian Vector Autoregression and Dynamic Stochastic General Equilibrium Models

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dc.contributor.author KRIWOLUZKY, Alexander
dc.date.accessioned 2009-09-09T10:39:39Z
dc.date.available 2009-09-09T10:39:39Z
dc.date.issued 2009
dc.identifier.issn 1725-6704
dc.identifier.uri http://hdl.handle.net/1814/12367
dc.description.abstract 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. en
dc.language.iso en en
dc.relation.ispartofseries EUI ECO en
dc.relation.ispartofseries 2009/29 en
dc.subject Bayesian Model Estimation en
dc.subject Vector Autoregression en
dc.subject Identification en
dc.subject C51 en
dc.title Matching Theory and Data: Bayesian Vector Autoregression and Dynamic Stochastic General Equilibrium Models en
dc.type Working Paper en
dc.neeo.contributor KRIWOLUZKY|Alexander|aut|
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