Arbeitspapier
Quantile-based inflation risk models
This paper proposes a new approach to extract quantile-based inflation risk measures using Quantile Autoregressive Distributed Lag Mixed-Frequency Data Sampling (QADL-MIDAS) regression models. We compare our models to a standard Quantile Auto-Regression (QAR) model and show that it delivers better quantile forecasts at several forecasting horizons. We use the QADL-MIDAS model to construct inflation risk measures proxying for uncertainty, third-moment dynamics and the risk of extreme inflation realizations. We find that these risk measures are linked to the future evolution of inflation and changes in the effective federal funds rate.
- Sprache
-
Englisch
- Erschienen in
-
Series: NBB Working Paper ; No. 349
- Klassifikation
-
Wirtschaft
Forecasting Models; Simulation Methods
Quantitative Policy Modeling
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
- Thema
-
regression quantiles
inflation risk
quantile forecasting
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Ghysels, Eric
Iania, Leonardo
Striaukas, Jonas
- Ereignis
-
Veröffentlichung
- (wer)
-
National Bank of Belgium
- (wo)
-
Brussels
- (wann)
-
2018
- 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
- Ghysels, Eric
- Iania, Leonardo
- Striaukas, Jonas
- National Bank of Belgium
Entstanden
- 2018
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