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The Austrian Business Cycle in the European Context
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135 a basic structure model approach. In order to obtain stationary time series necessary for extracting business cycle fluctuations ac- cording to the deviation cycle approach, they used two consecu- tively applied HP filters119• The following dating procedure was car- ried out by a Markov-switching model. The results for the classical business cycle show that in that case the conventional wisdom of flatter business cycles in the core countries is not supported by the study of Artis - Marcellino - Proi- etti (2004). The steepness as well as the duration of recessions is much higher than those found for Germany, Italy or the euro area as a whole. This leads to bigger losses of output during recessions than in other countries. The picture changes when one looks at the results for the devia- tion cycle approach. For Austria, the authors report an average duration of recessions of around 17 months, which is slightly higher than for Italy (16 months), but considerably lower than for Ger- many (20 months) or the whole euro area (23 months). When we compare these results with those of our study, it can be observed that the results concerning the length of recessions for first-order- differenced autCDE {which comes closest to the definition of in- dustrial production) are much higher, irrespective of whether we concentrate only on the common component included or not. The gap is reduced by looking at HP-filtered series and shows quite similar results for BK-filtered data. This is quite plausible, because Artis - Marcellino - Proietti (2004) employed some kind of band- pass filter. Our HP-filtered series show a duration of economic 119 As the HP-filter belongs to the class of high-pass filters, only low frequencies are filtered out. If two HP-filters with different smoothing properties are applied one af- ter the other, they can work like a band-pass filter. Nevertheless this sort of band- pass filtering works not as exactly as the Baxter-King filter. Especially higher fre- quencies but still within the business cycle frequency band are erroneously filtered out, whereas high frequencies outside the band remain within the series. Therefore, the leakage of this filter is much higher than the Baxter-King filter applied in our study.
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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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