Arbeitspapier
Google data in bridge equation models for German GDP
There has been increased interest in the use of "big data" when it comes to forecasting macroeconomic time series such as private consumption or unemployment. However, applications on forecasting GDP are rather rare. In this paper we incorporate Google search data into a Bridge Equation Model, a version of which usually belongs to the suite of forecasting models at central banks. We show how to integrate these big data information, emphasizing the appeal of the underlying model in this respect. As the choice of which Google search terms to add to which equation is crucial - for the forecasting performance itself as well as for the economic consistency of the implied relationships - we compare different (ad-hoc, factor and shrinkage) approaches in terms of their pseudo-real time out-of-sample forecast performance for GDP, various GDP components and monthly activity indicators. We find that there are indeed sizeable gains possible from using Google search data, whereby partial least squares and LASSO appear most promising. Also, the forecast potential of Google search terms vis-avis survey indicators seems th have increased in recent years, suggesting that their scope in this field of application could increase in the future.
- ISBN
-
978-3-95729-373-2
- Sprache
-
Englisch
- Erschienen in
-
Series: Bundesbank Discussion Paper ; No. 18/2017
- Klassifikation
-
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Forecasting Models; Simulation Methods
- Thema
-
Big Data
Bridge Equation Models
Forecasting
Principal Components Analysis
Partial Least Squares
LASSO
Boosting
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Götz, Thomas B.
Knetsch, Thomas A.
- Ereignis
-
Veröffentlichung
- (wer)
-
Deutsche Bundesbank
- (wo)
-
Frankfurt a. M.
- (wann)
-
2017
- 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
- Götz, Thomas B.
- Knetsch, Thomas A.
- Deutsche Bundesbank
Entstanden
- 2017
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