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:
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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