Arbeitspapier
The common and speci fic components of inflation expectation across European countries
Inflation expectation (IE) is often considered to be an important determinant of actual inflation in modern economic theory, we are interested in investigating the main risk factors that determine its dynamics. We fiirst apply a joint arbitrage-free term structure model across different European countries to obtain estimate for country-specific IE. Then we use the two-component and three-component models to capture the main risk factors. We discover that the extracted common trend for IE is an important driver for each country of interest. Moreover a spatial-temporal copula model is tted to account for the non-Gaussian dependency across countries. This paper aims to extract informative estimates for IE and provide good implications for monetary policies.
- Language
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Englisch
- Bibliographic citation
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Series: IRTG 1792 Discussion Paper ; No. 2020-023
- Classification
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Wirtschaft
Mathematical Methods
Estimation: General
Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
Price Level; Inflation; Deflation
Interest Rates: Determination, Term Structure, and Effects
- Subject
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in ation expectation
joint yield-curve modeling
factor model
common trend
spatial-temporal copulas
- Event
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Geistige Schöpfung
- (who)
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Chen, Shi
Härdle, Wolfgang Karl
Wang, Weining
- Event
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Veröffentlichung
- (who)
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Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
- (where)
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Berlin
- (when)
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2020
- Handle
- Last update
-
10.03.2025, 11:41 AM CET
Data provider
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Chen, Shi
- Härdle, Wolfgang Karl
- Wang, Weining
- Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
Time of origin
- 2020
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