Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/308098 
Autor:innen: 
Erscheinungsjahr: 
2025
Schriftenreihe/Nr.: 
Bank of Finland Research Discussion Papers No. 1/2025
Verlag: 
Bank of Finland, Helsinki
Zusammenfassung: 
This paper addresses the challenge of inflation forecasting by adopting a thick modeling approach that integrates forecasts from time- and frequency-domain models. Frequency-domain models excel at capturing long-term trends while also accounting for short-term fluctuations. Combining these models with traditional approaches leverages their complementary strengths, resulting in forecasts that consistently outperform individual methods, especially during periods of heightened inflation volatility. By pooling insights from diverse modeling frameworks, this study provides a robust and effective strategy for improving inflation forecasts across different horizons.
Schlagwörter: 
inflation forecasting
forecast combination
wavelets
Haar filter
time-varying parameters
Phillips curve
JEL: 
C32
C53
E31
E37
E43
E44
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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