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The Austrian business cycle in the European context /
Dating business cycle turning points is still an important task for economic policy decisions. This study does this for the Austrian economy for the period between 1976 and 2005, using only quarterly national accounts data of Austria, Germany and the euro area. Three different filtering methods are...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Frankfurt ; New York :
Peter Lang,
2008.
|
| Colección: | Forschungsergebnisse der Wirtschaftsuniversität Wien ;
Bd. 25. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover
- Zusammenfassung
- Abstract
- List of figures and tables
- List of abbreviations
- List of variables
- 1. Research motivation and overview
- 2. The data
- 3. Methods of extracting business cycle characteristics
- 3.1 Defining the business cycle
- 3.1.1 The classical business cycle definition
- 3.1.2 The deviation cycle definition
- 3.2 Isolation of business cycle frequencies
- 3.2.1 Outliers
- 3.2.2 Calendar effects
- 3.2.3 Seasonal variations
- 3.2.4 The trend
- 4. Identifying the business cycle
- 4.1 Construction of composite economic indices
- 4.1.1 The empirical NBER approach
- 4.1.2 Index models
- 4.2 Univariate determination of the business cycle
- 5. Analysing cyclical comovements
- 5.1 Time domain statistics for analysing comovements
- 5.2 Frequency domain statistics for analysing comovements
- 5.2.1 Coherence
- 5.2.2 Phase spectra and mean delay
- 5.2.3 Dynamic correlation
- 5.2.4 Cohesion
- 6. Dating the business cycle
- 6.1 The expert approaches
- 6.2 The Bry-Boschan routine
- 6.3 Hidden Markovian-switching processes
- 6.4 Threshold autoregressive models
- 7. Analysis of turning points
- 7.1 Mean and average leads and lags
- 7.2 Contingency tables for turning points
- 7.3 The intrinsic lead and lag classification of dynamic factor models
- 7.4 Concordance indicator
- 7.5 Standard deviation of the cycle
- 7.6 Mean absolute deviation
- 7.7 Triangle approximation
- 8. Results
- 8.1 Isolation of business cycle frequencies
- 8.1.1 First-order differences
- 8.1.2 The HP filter
- 8.1.3 The BK filter
- 8.2 Determination of the reference business cycle
- 8.2.1 Ad-hoc selection of the business cycle reference series
- 8.2.2 Determination of the business cycle by a dynamic factor model approach
- 8.3 Dating the business cycle.
- 8.3.1 Dating the business cycle in the ad-hoc selection framework
- 8.3.2 Dating the business cycle in the dynamic factor model framework
- 9. Comparing results with earlier studies on the Austrian business cycle
- 9.1 Comparing the results with the study by Altissimo et al. (2001)
- 9.2 Comparing the results with the study by Mönch
- Uhlig (2004)
- 9.3 Comparing the results with the study by Cheung
- Westermann (1999)
- 9.4 Comparing the results with the study by Brandner
- Neusser (1992)
- 9.5 Comparing the results with the study by Forni
- Hallin
- Lippi
- Reichlin (2000)
- 9.6 Comparing the results with the study by Breitung
- Eickmeier (2005)
- 9.7 Comparing the results with the study by Artis
- Marcellino
- Proietti (2004)
- 9.8 Comparing the results with the study by Vijselaar
- Albers (2001)
- 9.9 Comparing the results with the study by Artis
- Zhang (1999)
- 9.10 Comparing the results with the study by Dickerson
- Gibson
- Tsakalotos (1998)
- 9.11 Comparing the results with the study by Artis
- Krolzig
- Toro (2004)
- 9.12 Comparing the results with the dating calendar of the CEPR
- 9.13 Comparing the results with the study by Breuss (1984)
- 9.14 Comparing the results with the study by Hahn
- Walterskirchen (1992)
- 9.15 Comparison of the results of different dating procedures
- 9.15.1 Turning point dates of the Austrian business cycle
- 9.15.2 Turning point dates of the euro area business cycle
- 10. Concluding remarks
- References
- Annex.