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93
Table 2: Differences in cross-correlations'
BK minus HP HP minus fod BK minus fod
aufF --0.01 --0.06 --0.07
autCDE 0.06 0.21 0.27
autGDP 0.01 0.09 0.10
autGHI 0.01 0.13 0.14
autGVA 0.01 0.03 0.04
autJK --0.03 --0.05 --0.08
eurGDP 0.06 0.26 0.32
eurGDPex 0.08 0.21 0.29
gerCDE 0.03 0.26 0.29
gerF 0.09 0. 17 0.26
gerGDP 0.07 0.35 0.42
gerGHI 0.07 0.30 0.37
gerGVA 0.07 0.34 0.41
gerGVAex 0.07 0.33 0.40
gerJK 0.01 0.28 0.29
Sum 0.60 2.85 3.45
Source: Own calculations. - 1 For abbreviations used see the list of abbreviations on
page B.
8.2. 1.2 Coherence
A statistic closely related to the cross-correlation is the coherence,
given in the next column of Tables A la to c 106• Instead of showing
the linear comovement in the time series domain, it is defined in
the frequency domain using cross-spectra, as explained in chap-
ter 5, equation (23). The table shows the proportion of spectral
mass within the frequency band between 6 and 32 quarters after
smoothing the frequencies by a Bartlett spectral window of three
quarters' length. This gives triangular weights w (n) for the frequen-
cies which are calculated according to
106 As the cross-spectrum is also defined over complex values, only the modulus of
the squared cross-spectra is taken instead. The root of the resulting squared coher-
ence is used here.
The Austrian Business Cycle in the European Context
Forschungsergebnisse der Wirtschaftsuniversitat Wien
- Title
- The Austrian Business Cycle in the European Context
- Author
- Marcus Scheiblecker
- Publisher
- PETER LANG - lnternationaler Verlag der Wissenschaften
- Location
- Frankfurt
- Date
- 2008
- Language
- English
- License
- CC BY 4.0
- ISBN
- 978-3-631-75458-0
- Size
- 14.8 x 21.0 cm
- Pages
- 236
- Keywords
- Economy, Wirtschaft, WIFO, Vienna
- Categories
- International
- Recht und Politik
Table of contents
- Zusammenfassung V
- Abstract IX
- List of figures and tables XV
- List of abbreviations XVII
- List of variables XIX
- 1. Research motivation and overview 1
- 2. The data 7
- 3. Methods of extracting business cycle characteristics 13
- 4. Identifying the business cycle 41
- 5. Analysing cyclical comovements
- 6. Dating the business cycle 61
- 7. Analysis of turning points 71
- 8. Results 79
- 9. Comparing results with earlier studies on the Austrian business cycle 125
- 9.1 Comparing the results with the study by Altissimo et al. (2001) 126
- 9.2 Comparing the results with the study by Monch -Uhlig (2004) 128
- 9.3 Comparing the results with the study by Cheung -Westermann (1999) 130
- 9.4 Comparing the results with the study by Brandner -Neusser (1992) 131
- 9.5 Comparing the results with the study by Forni - Hallin -Lippi -Reich/in (2000) 132
- 9.6 Comparing the results with the study by Breitung -Eickmeier (2005) 134
- 9.7 Comparing the results with the study by Artis - Marcellino - Proietti (2004) 134
- 9.8 Comparing the results with the study by Vijselaar -Albers (2001) 140
- 9.9 Comparing the results with the study by Artis - Zhang (1999) 142
- 9.10 Comparing the results with the study by Dickerson -Gibson -Tsakalotos (1998) 142
- 9.11 Comparing the results with the study by Artis - Krolzig - Toro (2004) 143
- 9.12 Comparing the results with the dating calendar of the CEPR 146
- 9.13 Comparing the results with the study by Breuss ( 1984) 151
- 9.14 Comparing the results with the study by Hahn - Walterskirchen ( 1992) 153
- 9.15 Comparison of the results of different dating procedures 154
- 9 .15.1 Turning point dates of the Austrian business cycle 155
- 9 .15.2 Turning point dates of the euro area business cycle 156
- 10. Concludlng remarks 161
- References 169
- Annex 177