EconStor >
Forschungsinstitut zur Zukunft der Arbeit (IZA), Bonn >
IZA Discussion Papers, Forschungsinstitut zur Zukunft der Arbeit (IZA) >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/52065
  

Full metadata record

DC FieldValueLanguage
dc.contributor.authorKoop, Garyen_US
dc.contributor.authorPesaran, Hashemen_US
dc.contributor.authorSmith, Ron P.en_US
dc.date.accessioned2011-08-09en_US
dc.date.accessioned2011-11-23T11:43:14Z-
dc.date.available2011-11-23T11:43:14Z-
dc.date.issued2011en_US
dc.identifier.piurn:nbn:de:101:1-201104134513en_US
dc.identifier.urihttp://hdl.handle.net/10419/52065-
dc.description.abstractIn recent years there has been increasing concern about the identification of parameters in dynamic stochastic general equilibrium (DSGE) models. Given the structure of DSGE models it may be difficult to determine whether a parameter is identified. For the researcher using Bayesian methods, a lack of identification may not be evident since the posterior of a parameter of interest may differ from its prior even if the parameter is unidentified. We show that this can be the case even if the priors assumed on the structural parameters are independent. We suggest two Bayesian identification indicators that do not suffer from this difficulty and are relatively easy to compute. The first applies to DSGE models where the parameters can be partitioned into those that are known to be identified and the rest where it is not known whether they are identified. In such cases the marginal posterior of an unidentified parameter will equal the posterior expectation of the prior for that parameter conditional on the identified parameters. The second indicator is more generally applicable and considers the rate at which the posterior precision gets updated as the sample size (T) is increased. For identified parameters the posterior precision rises with T, whilst for an unidentified parameter its posterior precision may be updated but its rate of update will be slower than T. This result assumes that the identified parameters are √T-consistent, but similar differential rates of updates for identified and unidentified parameters can be established in the case of super consistent estimators. These results are illustrated by means of simple DSGE models.en_US
dc.language.isoengen_US
dc.publisherIZA Bonnen_US
dc.relation.ispartofseriesDiscussion paper series // Forschungsinstitut zur Zukunft der Arbeit 5638en_US
dc.subject.jelC11en_US
dc.subject.jelC15en_US
dc.subject.jelE17en_US
dc.subject.ddc330en_US
dc.subject.keywordBayesian identificationen_US
dc.subject.keywordDSGE modelsen_US
dc.subject.keywordposterior updatingen_US
dc.subject.keywordNew Keynesian Phillips Curveen_US
dc.subject.stwDynamisches Gleichgewichten_US
dc.subject.stwSchätztheorieen_US
dc.subject.stwBayes-Statistiken_US
dc.subject.stwNeukeynesianische Makroökonomiken_US
dc.subject.stwPhillips-Kurveen_US
dc.subject.stwTheorieen_US
dc.titleOn identification of Bayesian DSGE modelsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn665579225en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:IZA Discussion Papers, Forschungsinstitut zur Zukunft der Arbeit (IZA)

Files in This Item:
File Description SizeFormat
665579225.pdf316.25 kBAdobe PDF
No. of Downloads: Counter Stats
Show simple item record
Download bibliographical data as: BibTeX

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.