Advanced Search
MyIDEAS: Login

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. Anindya BANERJEE & Massimiliano MARCELLINO, 2002. "Are There Any Reliable Leading Indicators for US Inflation and GDP Growth?," Economics Working Papers ECO2002/21, European University Institute.
  2. 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., vol. 27(5), pages 371-390.
  3. Domenico Giannone & Lucrezia Reichlin & David Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
  4. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542, April.
  5. Jan J. J. Groen & George Kapetanios, 2008. "Revisiting useful approaches to data-rich macroeconomic forecasting," Staff Reports 327, Federal Reserve Bank of New York.
  6. Peter Grasmann & Filip Keereman, 2001. "An indicator-based short-term forecast for quarterly GDP in the euro area," European Economy - Economic Papers 154, Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission.
  7. 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, vol. 47(1), pages 1-18, February.
  8. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank, Research Centre.
  9. 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.
  10. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  11. 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, vol. 222(3), pages 316-336.
  12. Zadrozny, Peter, 1988. "Gaussian Likelihood of Continuous-Time ARMAX Models When Data Are Stocks and Flows at Different Frequencies," Econometric Theory, Cambridge University Press, vol. 4(01), pages 108-124, April.
  13. Angelini, Elena & Camba-Méndez, Gonzalo & Giannone, Domenico & Rünstler, Gerhard & Reichlin, Lucrezia, 2008. "Short-term forecasts of euro area GDP growth," Working Paper Series 0949, European Central Bank.
  14. Karim Barhoumi & Szilard Benk & Riccardo Cristadoro & Ard Den Reijer & Audrone Jakaitiene & Piotr Jelonek & António Rua & Gerhard Rünstler & Karsten Ruth & Christophe Van Nieuwenhuyze, 2008. "Short-term forecasting of GDP using large monthly datasets - a pseudo real-time forecast evaluation exercise," Occasional Paper Series 84, European Central Bank.
  15. 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.
  16. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics 11140, University of Munich, Department of Economics.
  17. 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, vol. 222(3), pages 289-315.
  18. 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.
  19. Jushan Bai & Serena Ng, 2009. "Boosting diffusion indices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 607-629.
  20. 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.
  21. David Hendry & Michael P. Clements, 2001. "Pooling of Forecasts," Economics Papers 2002-W9, Economics Group, Nuffield College, University of Oxford.
  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. Franck Sédillot & Nigel Pain, 2003. "Indicator Models of Real GDP Growth in Selected OECD Countries," OECD Economics Department Working Papers 364, OECD Publishing.
  25. repec:fth:eeccco:154 is not listed on IDEAS
  26. Wohlrabe, Klaus, 2009. "Forecasting with mixed-frequency time series models," Munich Dissertations in Economics 9681, University of Munich, Department of Economics.
  27. 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.
  28. 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.
  29. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
  30. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
  31. 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.
  32. Buhlmann P. & Yu B., 2003. "Boosting With the L2 Loss: Regression and Classification," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 324-339, January.
  33. Hahn, Elke & Skudelny, Frauke, 2008. "Early estimates of euro area real GDP growth: a bottom up approach from the production side," Working Paper Series 0975, European Central Bank.
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. 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.
  2. 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.
  3. 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.
  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. 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.
  6. 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.
  7. 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, June.
  8. Wolfgang Nierhaus, 2012. "Konjunkturprognosen heute – Möglichkeiten und Probleme," ifo Dresden berichtet, Ifo Institute for Economic Research at the University of Munich, vol. 19(05), pages 29-37, October.
  9. 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.

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.