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 2009-07-13T10:01:41Z
dc.date.available 2009-07-13T10:01:41Z
dc.date.issued 2009
dc.identifier.issn 1830-7728
dc.identifier.uri http://hdl.handle.net/1814/12052
dc.description 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. en
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.description.sponsorship Part of the research was conducted while I was visiting Princeton University funded by the German Academic Exchange Service. Further grants from the DEKA Bank and the SFB 649 are gratefully acknowledged. en
dc.language.iso en en
dc.relation.ispartofseries EUI MWP en
dc.relation.ispartofseries 2009/27 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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