المستودع الأكاديمي جامعة المدينة

Real-time forecasting of GDP based on a large factor model with monthly and quarterly data

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dc.creator Schumacher, Christian
dc.creator Breitung, Jörg
dc.date 2006
dc.date.accessioned 2013-10-16T07:06:11Z
dc.date.available 2013-10-16T07:06:11Z
dc.date.issued 2013-10-16
dc.identifier http://hdl.handle.net/10419/19662
dc.identifier ppn:519430387
dc.identifier RePEc:zbw:bubdp1:5097
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/10419/19662
dc.description This 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.language eng
dc.relation Discussion paper Series 1 / Volkswirtschaftliches Forschungszentrum der Deutschen Bundesbank 2006,33
dc.rights http://www.econstor.eu/dspace/Nutzungsbedingungen
dc.subject E37
dc.subject C53
dc.subject ddc:330
dc.subject monthly GDP
dc.subject EM algorithm
dc.subject principal components
dc.subject factor models
dc.subject Konjunkturprognose
dc.subject Prognoseverfahren
dc.subject Zeitreihenanalyse
dc.subject Faktorenanalyse
dc.subject Schätzung
dc.subject Theorie
dc.subject Deutschland
dc.title Real-time forecasting of GDP based on a large factor model with monthly and quarterly data
dc.type doc-type:workingPaper


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