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Deutsche Bundesbank, Forschungszentrum, Frankfurt am Main >
Discussion Paper Series 1: Economic Studies, Deutsche Bundesbank >
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http://hdl.handle.net/10419/19662
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| Title: | | Real-time forecasting of GDP based on a large factor model with monthly and quarterly data  |
| Authors: | | Schumacher, Christian Breitung, Jörg |
| Issue Date: | | 2006 |
| Series/Report no.: | | Discussion paper Series 1 / Volkswirtschaftliches Forschungszentrum der Deutschen Bundesbank 2006,33 |
| Abstract: | | 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. |
| Subjects: | | monthly GDP EM algorithm principal components factor models |
| JEL: | | E37 C53 |
| Document Type: | | Working Paper |
| Appears in Collections: | | Discussion Paper Series 1: Economic Studies, Deutsche Bundesbank
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