Page - 72 - in The Austrian Business Cycle in the European Context
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72
The calculation of means of leads and lags can also be done in
the frequency domain, looking at the cross-spectrum r( w) of both
series b and s98• As this in general takes on complex values as
shown in (23), it has to be transformed into polar coordinates
which yield
{36) Yb,s (a>)= lh., (w)jje-iPh(w)
with the argument Ph(w) indicating the shift in the number of peri-
ods as a multiple of the frequency for which it is observed {the so
called phase angle shift). Averaging over a certain frequency
band that lies between the boundaries w" and w1 by
(37) "'11 Ph(w)
f-w-dw
"'I
allows looking at leads and lags over this band. Positive values in-
dicate that the observed series z, is leading the reference series
zh, with negative values indicating lags.
7
.2 Contingency tables for turning points
Artis -Krolzig -Toro (2004) proposed a further method of analysing
business cycle comovements. With a binary variable indicating
whether the economy is expanding or contracting {which can be
derived from the turning points) they constructed 2 x 2 contin-
gency tables for each pair of series of the form of Table 1.
98 See Joint Research Centre of the European Commission ( 1993).
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