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Konstruktion von Indikatoren zur Analyse der wirtschaftlichen Aktivität in den Dienstleistungsbereichen

  • Klaus Wohlrabe

    ()

Der Bereich Dienstleistungen macht mehr als 70% der deutschen Bruttowertschöpfung aus, jedoch ist die Konjunkturanalyse- und Prognose in diesem Wirtschaftsbereich noch sehr unterentwickelt. Ein Blick in die Literatur zeigt, dass die Forschung hier noch am Anfang steht und sich bisher diesem Bereich nicht angenommen hat. Der vorliegende Forschungsbericht stellt einen ersten Ansatz zur Schließung dieser Lücke dar. Zunächst wurden Indikatoren für sechs verschiedene Teilbereiche des Dienstleistungssektors auf ihre Prognoseeigenschaften identifiziert. Hier hat sich gezeigt, dass nur sehr wenige potentielle Indikatoren vorliegen und diese teilweise eine erst recht junge Historie haben. Auf Basis dieses Datenbestandes wurden eine statische und dynamische Korrelationsanalyse, Wendepunktprognosen und ein Prognosewettbewerb bzgl. Punktprognosen durchgeführt. Die Ergebnisse sind teilweise erfolgsversprechend, sind jedoch mit Vorsicht zu interpretieren, da der Evaluierungszeitraum teilweise sehr kurz war. Deshalb wurden neben den Einzelindikatoren auch die Eigenschaften von synthetischen Indikatoren untersucht. Diese wurden auf Basis verschiedener Aggregationsmethoden (Korrelationen und ökonometrische Gewichte) der Einzelindikatoren gewonnen. In der Korrelationsanalyse konnten keine signifikanten Verbesserungen erzielt werden, jedoch wurden für die Prognose für alle Referenzreihen teilweise erhebliche Verbesserungen mit den synthetischen Indikatoren erzielt im Vergleich zum besten Einzelindikator.

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This book is provided by Ifo Institute for Economic Research at the University of Munich in its series ifo Forschungsberichte with number 55 and published in 2011.
Handle: RePEc:ces:ifofob:55
Contact details of provider: Postal: Poschingerstr. 5, 81679 München
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  1. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil II: Die Zyklendatierung," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 62(14), pages 24-31, 07.
  2. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
  3. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2010. "New Eurocoin: Tracking Economic Growth in Real Time," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1024-1034, November.
  4. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo, vol. 56(2), pages 192-220, June.
  5. Evan Koenig & Sheila Dolmas & Jeremy M. Piger, 2002. "The use and abuse of 'real-time' data in economic forecasting," Working Papers 2001-015, Federal Reserve Bank of St. Louis.
  6. Clements, Michael P & Galvão, Ana Beatriz, 2008. "Macroeconomic Forecasting With Mixed-Frequency Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 546-554.
  7. C�cile Denis & Kieran Mc Morrow & Werner R�ger, 2002. "Production function approach to calculating potential growth and output gaps - estimates for the EU Member States and the US," European Economy - Economic Papers 176, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
  8. Konstantin A. Kholodilin & Boriss Siliverstovs, 2006. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 226(3), pages 234-259, May.
  9. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1 National Bureau of Economic Research, Inc.
  10. Klaus Abberger & Klaus Wohlrabe, 2006. "Einige Prognoseeigenschaften des ifo Geschäftsklimas - Ein Überblick über die neuere wissenschaftliche Literatur," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
  11. Kai Carstensen & Steffen Henzel & Johannes Mayr & Klaus Wohlrabe, 2009. "IFOCAST: Methoden der ifo-Kurzfristprognose," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 62(23), pages 15-28, December.
  12. Christian Seiler & Klaus Wohlrabe, 2010. "RePEc – eine unabhängige Plattform zur wirtschaftswissenschaftlichen Output-Messung," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 63(07), pages 43-48, 04.
  13. Artis, Michael J & Kontolemis, Zenon G & Osborn, Denise R, 1997. "Business Cycles for G7 and European Countries," The Journal of Business, University of Chicago Press, vol. 70(2), pages 249-79, April.
  14. Michael Artis & Massimiliano Marcellino & Tommaso Proietti, 2004. "Dating Business Cycles: A Methodological Contribution with an Application to the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(4), pages 537-565, 09.
  15. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics 11140, University of Munich, Department of Economics.
  16. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
  17. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, 07.
  18. Klaus Wohlrabe, 2009. "Makroökonomische Prognosen mit gemischten Frequenzen," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
  19. Wohlrabe, Klaus, 2009. "Forecasting with mixed-frequency time series models," Munich Dissertations in Economics 9681, University of Munich, Department of Economics.
  20. Beate Schirwitz, 2009. "A comprehensive German business cycle chronology," Empirical Economics, Springer, vol. 37(2), pages 287-301, October.
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