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16 tion concept shows a lead in time vis-a-vis the one interpreted in the classical way. Furthermore, it has to be kept in mind that ap- plying the classical approach yields fewer and shorter contraction phases than the deviation method as documented in Harding - Pagan (2002). This may lead to a substantially different business cycle stabilisation policy. Especially the lead property makes de- viation cycle approaches more appropriate for economic policy issues. For all those reasons, the following analysis concentrates exclusively on the deviation cycle approach. 3.2 Isolation of business cycle frequencies Following Zarnowitz ( 1992), economic time series measuring output may be represented in the following form2a (1) Y, = X, +C, +S, +e, where x, represents the trend component, c, the business cycle variation and s, other components like seasonal, working day or weather effects. e, represents an error term capturing all residuals like special events and measurement errors. In earlier approaches, all components have been modelled as being deterministic, whereas modern ones understand all or some of them as stochas- tic processes29. 28 Frequently this model is specified in logarithms where the underlying model is multiplicative r, = X, • c, • s, • e, . 29 Examples for this kind of models are structural time series models following the approach of Harvey ( 1989) where the trend is modelled as a stochastic process. Also the method of using just growth rates (out of first order differencing process) which implies random walk behaviour of the trend component can be regarded as a stochastic approach.
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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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