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7.6 Mean absolute deviation
This measure is constructed similarly to the standard deviation
(42)
Instead of squaring all deviations from the mean (or trend, as in
our application) to render them positive for summing up, the
mean absolute deviation just cumulates absolute values of these
deviations. The use of absolute deviations instead of squared ones
should make this statistic more robust in that single large deviations
are not weighted by squares. However, Dickerson - Gibson - Tsa-
kalatos ( 1998) found no substantial difference between squared
and mean deviations in analysing demand components within the
European Union.
7.7 Triangle approximation
Harding - Pagan (2002) proposed a method of estimating the se-
verity/strength of recessions/expansions. They argue that business
cycle fluctuations are defined by their deviation from trend as well
as by their duration. Therefore, they approximated the area of half
of a lobe formed by a business cycle phase by a triangle:
(43) Cr; = 0.5 (D; A;)
with Cr; being the right-angled triangle approximating the area of
half a phase of a business cycle representing the cumulative de-
viations from cyclical neutrality, and D; and A; the duration and
amplitude of the i-th cycle. As the actual cumulative movements
(c;) deviate in practice from the triangle approximation Cr;• a fur-
ther index measuring excess cumulated movements was pro-
posed by the authors
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