Arbeitspapier
Forecasting inflation with the New Keynesian Phillips curve: Frequency matters
We show that the New Keynesian Phillips Curve (NKPC) outperforms standard benchmarks in forecasting U.S. inflation once frequency-domain information is taken into account. We do so by decomposing the time series (of inflation and its predictors) into several frequency bands and forecasting separately each frequency component of inflation. The largest statistically significant forecasting gains are achieved with a model that forecasts the lowest frequency component of inflation (corresponding to cycles longer than 16 years) flexibly using information from all frequency components of the NKPC inflation predictors. Its performance is particularly good in the returning to recovery from the Great Recession.
- ISBN
-
978-952-323-322-5
- Sprache
-
Englisch
- Erschienen in
-
Series: Bank of Finland Research Discussion Papers ; No. 4/2020
- Klassifikation
-
Wirtschaft
Forecasting Models; Simulation Methods
Price Level; Inflation; Deflation
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
- Thema
-
inflation forecasting
new Keynesian Phillips curve
frequency domain
wavelets
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Martins, Manuel Mota Freitas
Verona, Fabio
- Ereignis
-
Veröffentlichung
- (wer)
-
Bank of Finland
- (wo)
-
Helsinki
- (wann)
-
2020
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 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
- Martins, Manuel Mota Freitas
- Verona, Fabio
- Bank of Finland
Entstanden
- 2020
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