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2015-03-23Buch DOI: 10.18452/4571
Generalized Exogenous Processes in DSGE
dc.contributor.authorMeyer-Gohde, Alexander
dc.contributor.authorNeuhoff, Daniel
dc.date.accessioned2017-06-16T01:12:58Z
dc.date.available2017-06-16T01:12:58Z
dc.date.created2015-06-18
dc.date.issued2015-03-23
dc.date.submitted2015-03-23
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/5223
dc.description.abstractThe 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 order along with the associated parameters. We apply the method to the technology process in a canonical neoclassical growth model using post war US GDP data and fin that the posterior decisively rejects the standard AR(1) assumption in favor of higher order processes. While the posterior contains significan uncertainty regarding the exact order, it concentrates posterior density on hump-shaped impulse responses. A negative response of hours to a positive technology shock is within the posterior credible set when noninvertible MA representations are admitted.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectBayesian analysiseng
dc.subjectynamic stochastic general equilibrium modeleng
dc.subjectModel evaluationeng
dc.subjectARMAeng
dc.subjectReversible Jump Markov Chain Monte Carloeng
dc.subject.ddc310 Statistik
dc.subject.ddc330 Wirtschaft
dc.titleGeneralized Exogenous Processes in DSGE
dc.typebook
dc.subtitleA Bayesian Approach
dc.identifier.urnurn:nbn:de:kobv:11-100230830
dc.identifier.doihttp://dx.doi.org/10.18452/4571
local.edoc.container-titleSonderforschungsbereich 649: Ökonomisches Risiko
local.edoc.pages45
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2015
local.edoc.container-issue14
local.edoc.container-year2015
local.edoc.container-erstkatid2195055-6

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