Advanced Search
MyIDEAS: Login to save this article or follow this journal

IFOCAST: Methoden der ifo-Kurzfristprognose

Contents:

Author Info

  • Kai Carstensen
  • Steffen Henzel

    ()

  • Johannes Mayr
  • Klaus Wohlrabe

    ()

Abstract

Die Einschätzung und Vorhersage der gesamtwirtschaftlichen Situation im laufenden und im folgenden Quartal ist eine der zentralen Aufgaben der Konjunkturprognose. Das ifo Institut stützt sich bei seiner Kurzfristprognose des Bruttoinlandsprodukts auf den dreistufigen IFOCAST-Ansatz. In der ersten Stufe werden monatlich verfügbare Indikatoren, wie z.B. das ifo Geschäftsklima, extrapoliert und auf Quartalsebene aggregiert. Besonderes Augenmerk gilt dabei der Industrieproduktion, die mit Hilfe disaggregierter ifo-Umfragedaten fortgeschrieben wird. In einem zweiten Schritt wird die Bruttowertschöpfung der einzelnen Wirtschaftsbereiche mit Hilfe von Brückengleichungen prognostiziert. Im Rahmen eines Kombinationsansatzes wird eine Vielzahl von Modellen kombiniert, um dem Aspekt der Modellunsicherheit Rechnung zu tragen. In einem dritten Schritt werden die Quartalsprognosen einzelner Wirtschaftsbereiche anhand der ökonomischen Gewichte zur Prognose des Bruttoinlandsprodukts aggregiert. Es hat sich sowohl in der Prognoseliteratur als auch in der praktischen Umsetzung gezeigt, dass der gewählte Ansatz eine zuverlässige Kurzfristprognose liefert und flexibel genug ist, um auch extreme Entwicklungen gut aufzuzeigen. Zusätzlich zu diesem mehrstufigen Standardverfahren werden in diesem Artikel Mixed-Frequency-Modelle und Boosting-Algorithmen vorgestellt, welche den Standardansatz im Probebetrieb ergänzen.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.cesifo-group.de/portal/page/portal/DocBase_Content/ZS/ZS-ifo_Schnelldienst/zs-sd-2009/ifosd_2009_23_2.pdf
Download Restriction: no

Bibliographic Info

Article provided by Ifo Institute for Economic Research at the University of Munich in its journal ifo Schnelldienst.

Volume (Year): 62 (2009)
Issue (Month): 23 (December)
Pages: 15-28

as in new window
Handle: RePEc:ces:ifosdt:v:62:y:2009:i:23:p:15-28

Contact details of provider:
Postal: Poschingerstrasse 5, 81679 Munich, Germany
Phone: +49 (89) 9224-0
Fax: +49 (89) 985369
Email:
Web page: http://www.cesifo-group.de
More information through EDIRC

Related research

Keywords: Konjunkturprognose; Prognoseverfahren; Deutschland;

Find related papers by JEL classification:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers, C.E.P.R. Discussion Papers 5178, C.E.P.R. Discussion Papers.
  2. Felix Hüfner & Michael Schröder, 2002. "Prognosegehalt von ifo-Geschäftserwartungen und ZEW-Konjunkturerwartungen: Ein ökonometrischer Vergleich," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 222(3), pages 316-336.
  3. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," Economics Working Papers, European University Institute ECO2009/32, European University Institute.
  4. Ulrich Fritsche & Sabine Stephan, 2002. "Leading Indicators of German Business Cycles - An Assessment of Properties," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 222(3), pages 289-315.
  5. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP," Economics Working Papers, European University Institute ECO2009/13, European University Institute.
  6. Angelini, Elena & Camba-Mendez, Gonzalo & Giannone, Domenico & Reichlin, Lucrezia & Rünstler, Gerhard, 2008. "Short-term Forecasts of Euro Area GDP Growth," CEPR Discussion Papers, C.E.P.R. Discussion Papers 6746, C.E.P.R. Discussion Papers.
  7. Stefan Mittnik & Peter A. Zadrozny, 2004. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly IFO Business Conditions Data," CESifo Working Paper Series 1203, CESifo Group Munich.
  8. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, Elsevier, vol. 47(1), pages 1-18, February.
  9. 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.
  10. David Hendry & Michael Clements, 2001. "Pooling of Forecasts," Economics Series Working Papers, University of Oxford, Department of Economics 2002-W09, University of Oxford, Department of Economics.
  11. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
  12. Peter Grasmann & Filip Keereman, 2001. "An indicator-based short-term forecast for quarterly GDP in the euro area," European Economy - Economic Papers, Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission 154, Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission.
  13. G. Rünstler & K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze, 2008. "Short-Term Forecasting of GDP Using Large Monthly Datasets: A Pseudo Real-Time Forecast Evaluation Exercise," Bank of Lithuania Working Paper Series, Bank of Lithuania 1, Bank of Lithuania.
  14. Jan J.J. Groen & George Kapetanios, 2008. "Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting," Working Papers, Queen Mary, University of London, School of Economics and Finance 624, Queen Mary, University of London, School of Economics and Finance.
  15. Marie Diron, 2008. "Short-term forecasts of euro area real GDP growth: an assessment of real-time performance based on vintage data," Journal of Forecasting, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 27(5), pages 371-390.
  16. Clements, Michael P & Galvão, Ana Beatriz, 2008. "Macroeconomic Forecasting With Mixed-Frequency Data," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 26, pages 546-554.
  17. Jushan Bai & Serena Ng, 2009. "Boosting diffusion indices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 24(4), pages 607-629.
  18. Anindya Banerjee & Massimiliano Marcellino, 2003. "Are There Any Reliable Leading Indicators for U.S. Inflation and GDP Growth?," Working Papers, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University 236, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  19. Projektgruppe Gemeinschaftsdiagnose, 2009. "Gemeinschaftsdiagnose Frühjahr 2009: Im Sog der Weltrezession," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 62(08), pages 03-81, 04.
  20. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics, University of Munich, Department of Economics 11140, University of Munich, Department of Economics.
  21. 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, Anderson Graduate School of Management, UCLA qt9mf223rs, Anderson Graduate School of Management, UCLA.
  22. Jan Jacobs & Jan-Egbert Sturm, 2004. "Do Ifo Indicators Help Explain Revisions in German Industrial Production?," CESifo Working Paper Series 1205, CESifo Group Munich.
  23. Steffen Henzel & Johannes Mayr, 2009. "The Virtues of VAR Forecast Pooling – A DSGE Model Based Monte Carlo Study," Ifo Working Paper Series Ifo Working Paper No. 65, Ifo Institute for Economic Research at the University of Munich.
  24. Hahn, Elke & Skudelny, Frauke, 2008. "Early estimates of euro area real GDP growth: a bottom up approach from the production side," Working Paper Series, European Central Bank 0975, European Central Bank.
  25. Franck Sédillot & Nigel Pain, 2003. "Indicator Models of Real GDP Growth in Selected OECD Countries," OECD Economics Department Working Papers 364, OECD Publishing.
  26. Klaus Abberger & Wolfgang Nierhaus, 2008. "Die ifo Kapazitätsauslastung - ein gleichlaufender Indikator der deutschen Industriekonjunktur," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 61(16), pages 15-23, 08.
  27. 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.
  28. Zadrozny, Peter, 1988. "Gaussian Likelihood of Continuous-Time ARMAX Models When Data Are Stocks and Flows at Different Frequencies," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 4(01), pages 108-124, April.
  29. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, Elsevier, vol. 5(4), pages 559-583.
  30. repec:fth:eeccco:154 is not listed on IDEAS
  31. Wohlrabe, Klaus, 2009. "Forecasting with mixed-frequency time series models," Munich Dissertations in Economics, University of Munich, Department of Economics 9681, University of Munich, Department of Economics.
  32. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers, CIRANO 2004s-20, CIRANO.
  33. Buhlmann P. & Yu B., 2003. "Boosting With the L2 Loss: Regression and Classification," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 98, pages 324-339, January.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Robert Lehmann & Andreas Sharik & Michael Weber, 2014. "Der Erklärungsgehalt der regionalen ifo-Indikatoren am Beispiel der Industrie- und Bauumsätze," ifo Dresden berichtet, Ifo Institute for Economic Research at the University of Munich, Ifo Institute for Economic Research at the University of Munich, vol. 21(04), pages 18-24, 08.
  2. Klaus Wohlrabe, 2012. "Prognose des Dienstleistungssektors in Deutschland," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 65(01), pages 31-39, 01.
  3. Wolfgang Nierhaus, 2014. "Wirtschaftskonjunktur 2013: Prognose und Wirklichkeit," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 67(02), pages 41-46, 01.
  4. Steffen Henzel & Sebastian Rast, 2013. "Prognoseeigenschaften von Indikatoren zur Vorhersage des Bruttoinlandsprodukts in Deutschland," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 66(17), pages 39-46, 09.
  5. Roland Döhrn & Tobias Kitlinski & Martin Micheli & Torsten Schmidt & Simeon Vosen & György Barabas & Heinz Gebhardt & Lina Zimmermann, 2010. "Die wirtschaftliche Entwicklung im Inland zur Jahresmitte 2010 - Aufschwung verliert an Fahrt," RWI Konjunkturbericht, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, pages 46, 09.
  6. Klaus Wohlrabe, 2011. "Konstruktion von Indikatoren zur Analyse der wirtschaftlichen Aktivität in den Dienstleistungsbereichen," ifo Forschungsberichte, Ifo Institute for Economic Research at the University of Munich, number 55, 9.
  7. Christian Seiler & Klaus Wohlrabe, 2013. "Das ifo Geschäftsklima und die deutsche Konjunktur," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.
  8. Anna Billharz & Steffen Elstner & Marcus Jüppner, 2012. "Methoden der ifo Kurzfristprognose am Beispiel der Ausrüstungsinvestitionen," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 65(21), pages 24-33, November.
  9. Wolfgang Nierhaus, 2013. "Konjunkturprognosen heute – Möglichkeiten und Probleme," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 66(01), pages 25-32, 01.
  10. Steffen Henzel & Wolfgang Nierhaus & Tim Oliver Berg & Christian Breuer & Kai Carstensen & Christian Grimme & Oliver Hülsewig & Atanas Hristov & Nikolay Hristov & Michael Kleemann & Wolfgang Meister , 2013. "ifo Konjunkturprognose 2013/2014: Deutsche Konjunkturlokomotive kommt unter Dampf," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 66(24), pages 20-67, December.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:ces:ifosdt:v:62:y:2009:i:23:p:15-28. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Klaus Wohlrabe).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.