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  • 1
    Online Resource
    Online Resource
    Frankfurt a.M. :Peter Lang GmbH, Internationaler Verlag der Wissenschaften,
    UID:
    almahu_9949568485402882
    Format: 1 online resource (234 pages)
    Edition: 1st ed.
    ISBN: 9783631754580
    Series Statement: Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ; v.25
    Note: Cover -- Zusammenfassung -- Abstract -- List of figures and tables -- List of abbreviations -- List of variables -- 1. Research motivation and overview -- 2. The data -- 3. Methods of extracting business cycle characteristics -- 3.1 Defining the business cycle -- 3.1.1 The classical business cycle definition -- 3.1.2 The deviation cycle definition -- 3.2 Isolation of business cycle frequencies -- 3.2.1 Outliers -- 3.2.2 Calendar effects -- 3.2.3 Seasonal variations -- 3.2.4 The trend -- 4. Identifying the business cycle -- 4.1 Construction of composite economic indices -- 4.1.1 The empirical NBER approach -- 4.1.2 Index models -- 4.2 Univariate determination of the business cycle -- 5. Analysing cyclical comovements -- 5.1 Time domain statistics for analysing comovements -- 5.2 Frequency domain statistics for analysing comovements -- 5.2.1 Coherence -- 5.2.2 Phase spectra and mean delay -- 5.2.3 Dynamic correlation -- 5.2.4 Cohesion -- 6. Dating the business cycle -- 6.1 The expert approaches -- 6.2 The Bry-Boschan routine -- 6.3 Hidden Markovian-switching processes -- 6.4 Threshold autoregressive models -- 7. Analysis of turning points -- 7.1 Mean and average leads and lags -- 7.2 Contingency tables for turning points -- 7.3 The intrinsic lead and lag classification of dynamic factor models -- 7.4 Concordance indicator -- 7.5 Standard deviation of the cycle -- 7.6 Mean absolute deviation -- 7.7 Triangle approximation -- 8. Results -- 8.1 Isolation of business cycle frequencies -- 8.1.1 First-order differences -- 8.1.2 The HP filter -- 8.1.3 The BK filter -- 8.2 Determination of the reference business cycle -- 8.2.1 Ad-hoc selection of the business cycle reference series -- 8.2.2 Determination of the business cycle by a dynamic factor model approach -- 8.3 Dating the business cycle. , 8.3.1 Dating the business cycle in the ad-hoc selection framework -- 8.3.2 Dating the business cycle in the dynamic factor model framework -- 9. Comparing results with earlier studies on the Austrian business cycle -- 9.1 Comparing the results with the study by Altissimo et al. (2001) -- 9.2 Comparing the results with the study by Mönch - Uhlig (2004) -- 9.3 Comparing the results with the study by Cheung - Westermann (1999) -- 9.4 Comparing the results with the study by Brandner - Neusser (1992) -- 9.5 Comparing the results with the study by Forni - Hallin - Lippi - Reichlin (2000) -- 9.6 Comparing the results with the study by Breitung - Eickmeier (2005) -- 9.7 Comparing the results with the study by Artis - Marcellino - Proietti (2004) -- 9.8 Comparing the results with the study by Vijselaar - Albers (2001) -- 9.9 Comparing the results with the study by Artis - Zhang (1999) -- 9.10 Comparing the results with the study by Dickerson - Gibson - Tsakalotos (1998) -- 9.11 Comparing the results with the study by Artis - Krolzig - Toro (2004) -- 9.12 Comparing the results with the dating calendar of the CEPR -- 9.13 Comparing the results with the study by Breuss (1984) -- 9.14 Comparing the results with the study by Hahn - Walterskirchen (1992) -- 9.15 Comparison of the results of different dating procedures -- 9.15.1 Turning point dates of the Austrian business cycle -- 9.15.2 Turning point dates of the euro area business cycle -- 10. Concluding remarks -- References -- Annex.
    Additional Edition: Print version: Scheiblecker, Marcus The Austrian Business Cycle in the European Context Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften,c2008 ISBN 9783631576076
    Language: English
    Keywords: Electronic books. ; Electronic books ; Electronic books. ; History
    URL: JSTOR
    URL: OAPEN
    URL: OAPEN
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  • 2
    Book
    Book
    Frankfurt am Main [u.a.] : Lang
    UID:
    b3kat_BV035129341
    Format: XIX, 207 Seiten , Diagramme
    ISBN: 9783631576076
    Series Statement: Forschungsergebnisse der Wirtschaftsuniversität Wien 25
    Note: Literaturverz. S. 169 - 175
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-631-75458-0
    Language: English
    Keywords: Österreich ; Konjunkturzyklus ; Geschichte 1976-2005 ; Hochschulschrift
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Author information: Scheiblecker, Marcus 1967-
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  • 3
    Online Resource
    Online Resource
    Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften
    UID:
    almahu_9948168571102882
    Format: 1 online resource
    Edition: 1st, New ed.
    ISBN: 9783631754580
    Series Statement: Forschungsergebnisse der Wirtschaftsuniversität Wien 25
    Content: Dating business cycle turning points is still an important task for economic policy decisions. This study does this for the Austrian economy for the period between 1976 and 2005, using only quarterly national accounts data of Austria, Germany and the euro area. Three different filtering methods are applied: first-order differences, the Hodrick-Prescott filter, and the Baxter-King filter. To all of them, two different methods of determining the business cycle are applied: the ad-hoc determination of the business cycle and a dynamic factor model, taking into account the common variations of Austria, the euro area and the German business cycle movements. The results of both methods are dated by the Bry-Boschan algorithm in order to locate peaks and troughs of the cycle. The results are interpreted and compared to already exiting studies on the euro area and the Austrian business cycle.
    Note: Doctoral Thesis , Contents: Survey of robustness of different business cycle analysis methods – Determination of business cycle turning points for Austria, Germany, and the euro area.
    Additional Edition: ISBN 9783631576076
    Language: English
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  • 4
    Online Resource
    Online Resource
    Bern : Peter Lang International Academic Publishing Group | Frankfurt am Main, Germany :Peter Lang,
    UID:
    almahu_9949561002502882
    Format: 1 online resource (XIX, 207 pages) : , illustrations, charts; digital, PDF file(s).
    Edition: First edition.
    ISBN: 3-631-75458-2
    Series Statement: Forschungsergebnisse der Wirtschaftsuniversität Wien ; Band 25.
    Content: Dating business cycle turning points is still an important task for economic policy decisions. This study does this for the Austrian economy for the period between 1976 and 2005, using only quarterly national accounts data of Austria, Germany and the euro area. Three different filtering methods are applied: first-order differences, the Hodrick-Prescott filter, and the Baxter-King filter. To all of them, two different methods of determining the business cycle are applied: the ad-hoc determination of the business cycle and a dynamic factor model, taking into account the common variations of Austria, the euro area and the German business cycle movements. The results of both methods are dated by the Bry-Boschan algorithm in order to locate peaks and troughs of the cycle. The results are interpreted and compared to already exiting studies on the euro area and the Austrian business cycle.
    Note: Cover -- Zusammenfassung -- Abstract -- List of figures and tables -- List of abbreviations -- List of variables -- 1. Research motivation and overview -- 2. The data -- 3. Methods of extracting business cycle characteristics -- 3.1 Defining the business cycle -- 3.1.1 The classical business cycle definition -- 3.1.2 The deviation cycle definition -- 3.2 Isolation of business cycle frequencies -- 3.2.1 Outliers -- 3.2.2 Calendar effects -- 3.2.3 Seasonal variations -- 3.2.4 The trend -- 4. Identifying the business cycle -- 4.1 Construction of composite economic indices -- 4.1.1 The empirical NBER approach -- 4.1.2 Index models -- 4.2 Univariate determination of the business cycle -- 5. Analysing cyclical comovements -- 5.1 Time domain statistics for analysing comovements -- 5.2 Frequency domain statistics for analysing comovements -- 5.2.1 Coherence -- 5.2.2 Phase spectra and mean delay -- 5.2.3 Dynamic correlation -- 5.2.4 Cohesion -- 6. Dating the business cycle -- 6.1 The expert approaches -- 6.2 The Bry-Boschan routine -- 6.3 Hidden Markovian-switching processes -- 6.4 Threshold autoregressive models -- 7. Analysis of turning points -- 7.1 Mean and average leads and lags -- 7.2 Contingency tables for turning points -- 7.3 The intrinsic lead and lag classification of dynamic factor models -- 7.4 Concordance indicator -- 7.5 Standard deviation of the cycle -- 7.6 Mean absolute deviation -- 7.7 Triangle approximation -- 8. Results -- 8.1 Isolation of business cycle frequencies -- 8.1.1 First-order differences -- 8.1.2 The HP filter -- 8.1.3 The BK filter -- 8.2 Determination of the reference business cycle -- 8.2.1 Ad-hoc selection of the business cycle reference series -- 8.2.2 Determination of the business cycle by a dynamic factor model approach -- 8.3 Dating the business cycle. , 8.3.1 Dating the business cycle in the ad-hoc selection framework -- 8.3.2 Dating the business cycle in the dynamic factor model framework -- 9. Comparing results with earlier studies on the Austrian business cycle -- 9.1 Comparing the results with the study by Altissimo et al. (2001) -- 9.2 Comparing the results with the study by Mönch - Uhlig (2004) -- 9.3 Comparing the results with the study by Cheung - Westermann (1999) -- 9.4 Comparing the results with the study by Brandner - Neusser (1992) -- 9.5 Comparing the results with the study by Forni - Hallin - Lippi - Reichlin (2000) -- 9.6 Comparing the results with the study by Breitung - Eickmeier (2005) -- 9.7 Comparing the results with the study by Artis - Marcellino - Proietti (2004) -- 9.8 Comparing the results with the study by Vijselaar - Albers (2001) -- 9.9 Comparing the results with the study by Artis - Zhang (1999) -- 9.10 Comparing the results with the study by Dickerson - Gibson - Tsakalotos (1998) -- 9.11 Comparing the results with the study by Artis - Krolzig - Toro (2004) -- 9.12 Comparing the results with the dating calendar of the CEPR -- 9.13 Comparing the results with the study by Breuss (1984) -- 9.14 Comparing the results with the study by Hahn - Walterskirchen (1992) -- 9.15 Comparison of the results of different dating procedures -- 9.15.1 Turning point dates of the Austrian business cycle -- 9.15.2 Turning point dates of the euro area business cycle -- 10. Concluding remarks -- References -- Annex. , Also available in print form. , English
    Additional Edition: Print version: ISBN 9783631576076
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    Online Resource
    Online Resource
    Bern : Peter Lang International Academic Publishing Group | Frankfurt am Main, Germany :Peter Lang,
    UID:
    edocfu_9958982586102883
    Format: 1 online resource (XIX, 207 pages) : , illustrations, charts; digital, PDF file(s).
    Edition: First edition.
    ISBN: 3-631-75458-2
    Series Statement: Forschungsergebnisse der Wirtschaftsuniversität Wien ; Band 25.
    Content: Dating business cycle turning points is still an important task for economic policy decisions. This study does this for the Austrian economy for the period between 1976 and 2005, using only quarterly national accounts data of Austria, Germany and the euro area. Three different filtering methods are applied: first-order differences, the Hodrick-Prescott filter, and the Baxter-King filter. To all of them, two different methods of determining the business cycle are applied: the ad-hoc determination of the business cycle and a dynamic factor model, taking into account the common variations of Austria, the euro area and the German business cycle movements. The results of both methods are dated by the Bry-Boschan algorithm in order to locate peaks and troughs of the cycle. The results are interpreted and compared to already exiting studies on the euro area and the Austrian business cycle.
    Note: Cover -- Zusammenfassung -- Abstract -- List of figures and tables -- List of abbreviations -- List of variables -- 1. Research motivation and overview -- 2. The data -- 3. Methods of extracting business cycle characteristics -- 3.1 Defining the business cycle -- 3.1.1 The classical business cycle definition -- 3.1.2 The deviation cycle definition -- 3.2 Isolation of business cycle frequencies -- 3.2.1 Outliers -- 3.2.2 Calendar effects -- 3.2.3 Seasonal variations -- 3.2.4 The trend -- 4. Identifying the business cycle -- 4.1 Construction of composite economic indices -- 4.1.1 The empirical NBER approach -- 4.1.2 Index models -- 4.2 Univariate determination of the business cycle -- 5. Analysing cyclical comovements -- 5.1 Time domain statistics for analysing comovements -- 5.2 Frequency domain statistics for analysing comovements -- 5.2.1 Coherence -- 5.2.2 Phase spectra and mean delay -- 5.2.3 Dynamic correlation -- 5.2.4 Cohesion -- 6. Dating the business cycle -- 6.1 The expert approaches -- 6.2 The Bry-Boschan routine -- 6.3 Hidden Markovian-switching processes -- 6.4 Threshold autoregressive models -- 7. Analysis of turning points -- 7.1 Mean and average leads and lags -- 7.2 Contingency tables for turning points -- 7.3 The intrinsic lead and lag classification of dynamic factor models -- 7.4 Concordance indicator -- 7.5 Standard deviation of the cycle -- 7.6 Mean absolute deviation -- 7.7 Triangle approximation -- 8. Results -- 8.1 Isolation of business cycle frequencies -- 8.1.1 First-order differences -- 8.1.2 The HP filter -- 8.1.3 The BK filter -- 8.2 Determination of the reference business cycle -- 8.2.1 Ad-hoc selection of the business cycle reference series -- 8.2.2 Determination of the business cycle by a dynamic factor model approach -- 8.3 Dating the business cycle. , 8.3.1 Dating the business cycle in the ad-hoc selection framework -- 8.3.2 Dating the business cycle in the dynamic factor model framework -- 9. Comparing results with earlier studies on the Austrian business cycle -- 9.1 Comparing the results with the study by Altissimo et al. (2001) -- 9.2 Comparing the results with the study by Mönch - Uhlig (2004) -- 9.3 Comparing the results with the study by Cheung - Westermann (1999) -- 9.4 Comparing the results with the study by Brandner - Neusser (1992) -- 9.5 Comparing the results with the study by Forni - Hallin - Lippi - Reichlin (2000) -- 9.6 Comparing the results with the study by Breitung - Eickmeier (2005) -- 9.7 Comparing the results with the study by Artis - Marcellino - Proietti (2004) -- 9.8 Comparing the results with the study by Vijselaar - Albers (2001) -- 9.9 Comparing the results with the study by Artis - Zhang (1999) -- 9.10 Comparing the results with the study by Dickerson - Gibson - Tsakalotos (1998) -- 9.11 Comparing the results with the study by Artis - Krolzig - Toro (2004) -- 9.12 Comparing the results with the dating calendar of the CEPR -- 9.13 Comparing the results with the study by Breuss (1984) -- 9.14 Comparing the results with the study by Hahn - Walterskirchen (1992) -- 9.15 Comparison of the results of different dating procedures -- 9.15.1 Turning point dates of the Austrian business cycle -- 9.15.2 Turning point dates of the euro area business cycle -- 10. Concluding remarks -- References -- Annex. , Also available in print form. , English
    Additional Edition: Print version: ISBN 9783631576076
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 6
    Online Resource
    Online Resource
    Bern : Peter Lang International Academic Publishing Group | Frankfurt am Main, Germany :Peter Lang,
    UID:
    edoccha_9958982586102883
    Format: 1 online resource (XIX, 207 pages) : , illustrations, charts; digital, PDF file(s).
    Edition: First edition.
    ISBN: 3-631-75458-2
    Series Statement: Forschungsergebnisse der Wirtschaftsuniversität Wien ; Band 25.
    Content: Dating business cycle turning points is still an important task for economic policy decisions. This study does this for the Austrian economy for the period between 1976 and 2005, using only quarterly national accounts data of Austria, Germany and the euro area. Three different filtering methods are applied: first-order differences, the Hodrick-Prescott filter, and the Baxter-King filter. To all of them, two different methods of determining the business cycle are applied: the ad-hoc determination of the business cycle and a dynamic factor model, taking into account the common variations of Austria, the euro area and the German business cycle movements. The results of both methods are dated by the Bry-Boschan algorithm in order to locate peaks and troughs of the cycle. The results are interpreted and compared to already exiting studies on the euro area and the Austrian business cycle.
    Note: Cover -- Zusammenfassung -- Abstract -- List of figures and tables -- List of abbreviations -- List of variables -- 1. Research motivation and overview -- 2. The data -- 3. Methods of extracting business cycle characteristics -- 3.1 Defining the business cycle -- 3.1.1 The classical business cycle definition -- 3.1.2 The deviation cycle definition -- 3.2 Isolation of business cycle frequencies -- 3.2.1 Outliers -- 3.2.2 Calendar effects -- 3.2.3 Seasonal variations -- 3.2.4 The trend -- 4. Identifying the business cycle -- 4.1 Construction of composite economic indices -- 4.1.1 The empirical NBER approach -- 4.1.2 Index models -- 4.2 Univariate determination of the business cycle -- 5. Analysing cyclical comovements -- 5.1 Time domain statistics for analysing comovements -- 5.2 Frequency domain statistics for analysing comovements -- 5.2.1 Coherence -- 5.2.2 Phase spectra and mean delay -- 5.2.3 Dynamic correlation -- 5.2.4 Cohesion -- 6. Dating the business cycle -- 6.1 The expert approaches -- 6.2 The Bry-Boschan routine -- 6.3 Hidden Markovian-switching processes -- 6.4 Threshold autoregressive models -- 7. Analysis of turning points -- 7.1 Mean and average leads and lags -- 7.2 Contingency tables for turning points -- 7.3 The intrinsic lead and lag classification of dynamic factor models -- 7.4 Concordance indicator -- 7.5 Standard deviation of the cycle -- 7.6 Mean absolute deviation -- 7.7 Triangle approximation -- 8. Results -- 8.1 Isolation of business cycle frequencies -- 8.1.1 First-order differences -- 8.1.2 The HP filter -- 8.1.3 The BK filter -- 8.2 Determination of the reference business cycle -- 8.2.1 Ad-hoc selection of the business cycle reference series -- 8.2.2 Determination of the business cycle by a dynamic factor model approach -- 8.3 Dating the business cycle. , 8.3.1 Dating the business cycle in the ad-hoc selection framework -- 8.3.2 Dating the business cycle in the dynamic factor model framework -- 9. Comparing results with earlier studies on the Austrian business cycle -- 9.1 Comparing the results with the study by Altissimo et al. (2001) -- 9.2 Comparing the results with the study by Mönch - Uhlig (2004) -- 9.3 Comparing the results with the study by Cheung - Westermann (1999) -- 9.4 Comparing the results with the study by Brandner - Neusser (1992) -- 9.5 Comparing the results with the study by Forni - Hallin - Lippi - Reichlin (2000) -- 9.6 Comparing the results with the study by Breitung - Eickmeier (2005) -- 9.7 Comparing the results with the study by Artis - Marcellino - Proietti (2004) -- 9.8 Comparing the results with the study by Vijselaar - Albers (2001) -- 9.9 Comparing the results with the study by Artis - Zhang (1999) -- 9.10 Comparing the results with the study by Dickerson - Gibson - Tsakalotos (1998) -- 9.11 Comparing the results with the study by Artis - Krolzig - Toro (2004) -- 9.12 Comparing the results with the dating calendar of the CEPR -- 9.13 Comparing the results with the study by Breuss (1984) -- 9.14 Comparing the results with the study by Hahn - Walterskirchen (1992) -- 9.15 Comparison of the results of different dating procedures -- 9.15.1 Turning point dates of the Austrian business cycle -- 9.15.2 Turning point dates of the euro area business cycle -- 10. Concluding remarks -- References -- Annex. , Also available in print form. , English
    Additional Edition: Print version: ISBN 9783631576076
    Language: English
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