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147 The main differences between the approach of the NBER and the CEPR are that the latter uses quarterly data instead of monthly se- ries. Furthermore, the business cycle reflected in individual coun- tries plays a role in the dating procedure, too, which is not the case for the US. Seasonally adjusted GDP data seem to play the most important role for the CEPR method, without being the only ones. This imprecise definition of the business cycle, as in the case of the NBER, leaves large room for individual interpretation. A concentra- tion on growth rates alone (growth rate cycles) would imply that no distinction is made between trend or cycle growth rates. This reveals the adherence to the classical business cycle definition, if growth rates are not adjusted by their mean. But the CEPR stresses that looking at growth rates is not a fixed rule in its dating proce- dure. Nevertheless, focusing on growth rate cycles contains all the problems described in the theoretical chapter above, with the great disadvantage that the irregular component is superimposed making a reasonable dating nearly impossible. This danger is somewhat reduced by the criterion of two consecutive quarters of negative growth, but still there is no distinction between trend and business cycle growth. As it became apparent in our calculations on the basis of first- order-differenced series, fewer turning points have been detected than with other filtering methods. Here, the reason was that the Bry-Boschan dating algorithm recognises only turning points if there is no other contradictory information in close neighbour- hood. In the case of the CEPR method, the inclusion of trend growth rates shifts growth rates into the positive area, which re- duces considerably the number of turning points. In this way, the concept comes closer to the classical definition of the business cycle. It is therefore not surprising that the CEPR found only three complete cycles between 1970 and 2003. The first peak is dated at the third quarter of 197 4, with a following trough in 1Q1975. This cycle is outside the period analysed in the
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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

  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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