Arbeitspapier
A dynamic factor model for nowcasting Canadian GDP growth
This paper estimates a dynamic factor model (DFM) for nowcasting Canadian gross domestic product. The model is estimated with a mix of soft and hard indicators, and it features a high share of international data. The model is then used to generate nowcasts, predictions of the recent past and current state of the economy. In a pseudo real-time setting, we show that the DFM outperforms univariate benchmarks as well as other commonly used nowcasting models, such as mixed-data sampling (MIDAS) and bridge regressions.
- Sprache
-
Englisch
- Erschienen in
-
Series: Bank of Canada Staff Working Paper ; No. 2017-2
- Klassifikation
-
Wirtschaft
Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Forecasting Models; Simulation Methods
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
- Thema
-
Econometric and statistical methods
Business fluctuations and cycles
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Chernis, Tony
Sekkel, Rodrigo
- Ereignis
-
Veröffentlichung
- (wer)
-
Bank of Canada
- (wo)
-
Ottawa
- (wann)
-
2017
- DOI
-
doi:10.34989/swp-2017-2
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 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.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Chernis, Tony
- Sekkel, Rodrigo
- Bank of Canada
Entstanden
- 2017
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