Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10419/19662
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dc.creatorSchumacher, Christian-
dc.creatorBreitung, Jörg-
dc.date2006-
dc.date.accessioned2013-10-16T07:06:11Z-
dc.date.available2013-10-16T07:06:11Z-
dc.date.issued2013-10-16-
dc.identifierhttp://hdl.handle.net/10419/19662-
dc.identifierppn:519430387-
dc.identifierRePEc:zbw:bubdp1:5097-
dc.identifier.urihttp://koha.mediu.edu.my:8181/xmlui/handle/10419/19662-
dc.descriptionThis 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.-
dc.languageeng-
dc.relationDiscussion paper Series 1 / Volkswirtschaftliches Forschungszentrum der Deutschen Bundesbank 2006,33-
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.subjectE37-
dc.subjectC53-
dc.subjectddc:330-
dc.subjectmonthly GDP-
dc.subjectEM algorithm-
dc.subjectprincipal components-
dc.subjectfactor models-
dc.subjectKonjunkturprognose-
dc.subjectPrognoseverfahren-
dc.subjectZeitreihenanalyse-
dc.subjectFaktorenanalyse-
dc.subjectSchätzung-
dc.subjectTheorie-
dc.subjectDeutschland-
dc.titleReal-time forecasting of GDP based on a large factor model with monthly and quarterly data-
dc.typedoc-type:workingPaper-
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