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Author Scheiblecker, Marcus, 1967-

Title The Austrian business cycle in the European context / Marcus Scheiblecker
Published Frankfurt ; New York : Peter Lang, 2008

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Description 1 electronic resource (xix, 207 pages )
Series Forschungsergebnisse der Wirtschaftsuniversitat Wien ; Bd. 25
Forschungsergebnisse der Wirtschaftsuniversität Wien ; Bd. 25.
Contents 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
Summary 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
Analysis Austrian
Business
Context
Cycle
European
Geschichte 1976-2005
Konjunktur
Konjunkturanalyse
Konjunkturzyklus
Österreich
Scheiblecker
Bibliography Includes bibliographical references (pages 169-175)
Notes Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212 MiAaHDL
Description based on print version record; resource not viewed
digitized 2014 HathiTrust Digital Library committed to preserve pda MiAaHDL
In Books at JSTOR: Open Access JSTOR
OAPEN (Open Access Publishing in European Networks) OAPEN
Subject Business cycles -- Austria -- History -- 20th century
Business cycles -- Austria -- History -- 21st century
Business cycles -- European Union countries -- History
Business cycles -- Germany -- History
Business cycles
Konjunkturzyklus -- Österreich -- Geschichte 1976-2005.
Konjunkturzyklus
Austria
European Union countries
Germany
Österreich -- Konjunkturzyklus -- Geschichte 1976-2005.
Österreich
Genre/Form Electronic books
History
Form Electronic book
LC no. 2021758437
ISBN 9783631754580
3631754582