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166 Boschan routine, as compared with just filtered series. This is quite in line with theory, as the dynamic factor model is used for clean- ing idiosyncratic cycles. Only in the case of first-order-differenced series, the number of cycles detected increases. This can be ex- plained by the fact that the large number of ups and downs of just first-order-filtered time series is reduced by the dynamic factor model by idiosyncratic ones. This reduction led to a lower number of local minima and maxima, making it easier for the Bry-Boschan routine to locate them. Therefore, the BK-filter approach seems to be for theoretical as well as for practical reasons, the superior preparation for dating a cycle. Comparing the dating calendars for the Austrian business cycle of just BK-filtered series with the ones represented by their common component, one can observe that the number of cycles is lower in the latter case. A short- lived cycle reflected in just fil- tered Austrian gross value added (without agriculture and forestry) starting with a trough in 3Q 1983 and a following peak one year later has been recognised as of idiosyncratic nature and was therefore filtered out. The absence of this cycle for that period is confirmed by all studies compared with in chapter 9. They neither show this cycle for the euro area nor for Austria 130• There is only one further significant difference between just BK- filtered series and the ones transformed by the dynamic factor model, namely a trough following the peak around the change of the year 1994-1995. Whereas this is dated in the first case in the second quarter of 1997, it is located in the first quarter of 1999 by the common component approach. To check this again, results are compared with other studies. Unfortunately, only one of the studies presented in chapter 9 can be compared for this time span. Artis - Marcellino - Proietti (2004) confirm both troughs and 130 Only three studies provide a comparable dating calendar: Artis - Krolzig - Toro (2004), Hahn -Walterskirchen (1992) and the dating calendar for the euro area by the CEPR.
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The Austrian Business Cycle in the European Context
Forschungsergebnisse der Wirtschaftsuniversitat Wien
Titel
The Austrian Business Cycle in the European Context
Autor
Marcus Scheiblecker
Verlag
PETER LANG - lnternationaler Verlag der Wissenschaften
Ort
Frankfurt
Datum
2008
Sprache
englisch
Lizenz
CC BY 4.0
ISBN
978-3-631-75458-0
Abmessungen
14.8 x 21.0 cm
Seiten
236
Schlagwörter
Economy, Wirtschaft, WIFO, Vienna
Kategorien
International
Recht und Politik

Inhaltsverzeichnis

  1. Zusammenfassung V
  2. Abstract IX
  3. List of figures and tables XV
  4. List of abbreviations XVII
  5. List of variables XIX
  6. 1. Research motivation and overview 1
  7. 2. The data 7
  8. 3. Methods of extracting business cycle characteristics 13
    1. 3. 1 Defining the business cycle 13
      1. 3. 1 . 1 The classical business cycle definition 13
      2. 3.1.2 The deviation cycle definition 15
    2. 3.2 Isolation of business cycle frequencies 16
      1. 3.2. l Outliers 18
      2. 3.2.2 Calendar effects 20
      3. 3.2.3 Seasonal variations 21
      4. 3.2.4 The trend 23
  9. 4. Identifying the business cycle 41
    1. 4.1 Construction of composite economic indices 42
      1. 4. l . l The empirical NBER approach 42
      2. 4.1 .2 Index models 44
    2. 4.2 Univariate determination of the business cycle 52
  10. 5. Analysing cyclical comovements
    1. 5. 1 Time domain statistics for analysing comovements 55
    2. 5.2 Frequency domain statistics for analysing comovements 56
      1. 5.2.1 Coherence 57
      2. 5.2.2 Phase spectra and mean delay 58
      3. 5.2.3 Dynamic correlation 58
      4. 5.2.4 Cohesion 59
  11. 6. Dating the business cycle 61
    1. 6.1 The expert approaches 63
    2. 6.2 The Bry-Boschan routine 65
    3. 6.3 Hidden Markovian-switching processes 67
    4. 6.4 Threshold autoregressive models 69
  12. 7. Analysis of turning points 71
    1. 7.1 Mean and average leads and lags 71
    2. 7.2 Contingency tab/es for turning points 72
    3. 7.3 The intrinsic lead and lag classification of dynamic factor models 74
    4. 7.4 Concordance indicator 74
    5. 7.5 Standard deviation of the cycle 75
    6. 7.6 Mean absolute deviation 76
    7. 7.7 Triangle approximation 76
  13. 8. Results 79
    1. 8.1 Isolation of business cycle frequencies 79
      1. 8.1.1 First-order differences 79
      2. 8.1.2 The HP filter 80
      3. 8.1.3 The BK filter 80
    2. 8.2 Determination of the reference business cycle 85
      1. 8.2.1 Ad-hoc selection of the business cycle reference series 86
      2. 8.2.2 Determination of the business cycle by a dynamic factor model approach 97
    3. 8.3 Dating the business cycle 104
      1. 8.3.1 Dating the business cycle in the ad-hoc selection framework 104
      2. 8.3.2 Dating the business cycle in the dynamic factor model framework 115
  14. 9. Comparing results with earlier studies on the Austrian business cycle 125
    1. 9.1 Comparing the results with the study by Altissimo et al. (2001) 126
    2. 9.2 Comparing the results with the study by Monch -Uhlig (2004) 128
    3. 9.3 Comparing the results with the study by Cheung -Westermann (1999) 130
    4. 9.4 Comparing the results with the study by Brandner -Neusser (1992) 131
    5. 9.5 Comparing the results with the study by Forni - Hallin -Lippi -Reich/in (2000) 132
    6. 9.6 Comparing the results with the study by Breitung -Eickmeier (2005) 134
    7. 9.7 Comparing the results with the study by Artis - Marcellino - Proietti (2004) 134
    8. 9.8 Comparing the results with the study by Vijselaar -Albers (2001) 140
    9. 9.9 Comparing the results with the study by Artis - Zhang (1999) 142
    10. 9.10 Comparing the results with the study by Dickerson -Gibson -Tsakalotos (1998) 142
    11. 9.11 Comparing the results with the study by Artis - Krolzig - Toro (2004) 143
    12. 9.12 Comparing the results with the dating calendar of the CEPR 146
    13. 9.13 Comparing the results with the study by Breuss ( 1984) 151
    14. 9.14 Comparing the results with the study by Hahn - Walterskirchen ( 1992) 153
    15. 9.15 Comparison of the results of different dating procedures 154
    16. 9 .15.1 Turning point dates of the Austrian business cycle 155
    17. 9 .15.2 Turning point dates of the euro area business cycle 156
  15. 10. Concludlng remarks 161
  16. References 169
  17. Annex 177
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