Arbeitspapier
Real-time forecasting of GDP based on a large factor model with monthly and quarterly data
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Discussion Paper Series 1 ; No. 2006,33
- Klassifikation
-
Wirtschaft
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
Forecasting Models; Simulation Methods
- Thema
-
monthly GDP
EM algorithm
principal components
factor models
Konjunkturprognose
Prognoseverfahren
Zeitreihenanalyse
Faktorenanalyse
Schätzung
Theorie
Deutschland
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Schumacher, Christian
Breitung, Jörg
- Ereignis
-
Veröffentlichung
- (wer)
-
Deutsche Bundesbank
- (wo)
-
Frankfurt a. M.
- (wann)
-
2006
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Schumacher, Christian
- Breitung, Jörg
- Deutsche Bundesbank
Entstanden
- 2006
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