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dc.contributor.authorSchumacher, Christianen
dc.contributor.authorBreitung, Jörgen
dc.date.accessioned2009-01-28T16:01:49Z-
dc.date.available2009-01-28T16:01:49Z-
dc.date.issued2006-
dc.identifier.urihttp://hdl.handle.net/10419/19662-
dc.description.abstractThis paper discusses a factor model for estimating monthly GDP using a large number of monthly and quarterly time series in real-time. To take into account the different periodicities of the data and missing observations at the end of the sample, the factors are estimated by applying an EM algorithm combined with a principal components estimator. We discuss the in-sample properties of the estimator in real-time environments and methods for out-of-sample forecasting. As an empirical application, we estimate monthly German GDP in real-time, discuss the nowcast and forecast accuracy of the model and the role of revisions. Furthermore, we assess the contribution of timely monthly data to the forecast performance.en
dc.language.isoengen
dc.publisher|aDeutsche Bundesbank |cFrankfurt a. M.en
dc.relation.ispartofseries|aDiscussion Paper Series 1 |x2006,33en
dc.subject.jelE37en
dc.subject.jelC53en
dc.subject.ddc330en
dc.subject.keywordmonthly GDPen
dc.subject.keywordEM algorithmen
dc.subject.keywordprincipal componentsen
dc.subject.keywordfactor modelsen
dc.subject.stwKonjunkturprognoseen
dc.subject.stwPrognoseverfahrenen
dc.subject.stwZeitreihenanalyseen
dc.subject.stwFaktorenanalyseen
dc.subject.stwSchätzungen
dc.subject.stwTheorieen
dc.subject.stwDeutschlanden
dc.titleReal-time forecasting of GDP based on a large factor model with monthly and quarterly data-
dc.typeWorking Paperen
dc.identifier.ppn519430387en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:bubdp1:5097en

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