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http://hdl.handle.net/10419/19662
  

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dc.contributor.authorSchumacher, Christianen_US
dc.contributor.authorBreitung, Jörgen_US
dc.date.accessioned2009-01-28T16:01:49Z-
dc.date.available2009-01-28T16:01:49Z-
dc.date.issued2006en_US
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_US
dc.language.isoengen_US
dc.relation.ispartofseriesDiscussion paper Series 1 / Volkswirtschaftliches Forschungszentrum der Deutschen Bundesbank 2006,33en_US
dc.subject.jelE37en_US
dc.subject.jelC53en_US
dc.subject.ddc330en_US
dc.subject.keywordmonthly GDPen_US
dc.subject.keywordEM algorithmen_US
dc.subject.keywordprincipal componentsen_US
dc.subject.keywordfactor modelsen_US
dc.subject.stwKonjunkturprognoseen_US
dc.subject.stwPrognoseverfahrenen_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwFaktorenanalyseen_US
dc.subject.stwSchätzungen_US
dc.subject.stwTheorieen_US
dc.subject.stwDeutschlanden_US
dc.titleReal-time forecasting of GDP based on a large factor model with monthly and quarterly dataen_US
dc.typeWorking Paperen_US
dc.identifier.ppn519430387en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:bubdp1:5097-
Appears in Collections:Discussion Paper Series 1: Economic Studies, Deutsche Bundesbank

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