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Makroökonomische Prognosen mit gemischten Frequenzen

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  • Klaus Wohlrabe

Abstract

Die Prognose von makroökonomischen Zeitreihen steht häufig vor dem Problem, dass die verwendeten Indikatoren und die Zielzeitreihe in verschiedenen Frequenzen vorliegen. So ist das Bruttoinlandsprodukt nur auf Quartalsbasis verfügbar, während die meisten Indikatoren, wie z.B. das ifo Geschäftsklima, monatlich erhoben werden. Der vorliegende Artikel stellt zwei Modellklassen aus der neueren Literatur vor, die Schätzungen mit gemischten Frequenzen ohne aggregationsbedingten Informationsverlust erlauben: MIDAS-Modelle und VAR-Zustandsraummodelle. Diese Verfahren haben den Vorteil, dass hochfrequente Informationen, die innerhalb einer Periode hinzukommen, in die Prognose einbezogen werden können. Anhand einer Fallstudie für das deutsche BIP wird gezeigt, dass die neuen Modellklassen genauere Prognosen als die üblichen Zeitreihenmodelle liefern. Die neuen Verfahren werden am ifo Institut zur Kurzfristprognose eingesetzt.

Suggested Citation

  • Klaus Wohlrabe, 2009. "Makroökonomische Prognosen mit gemischten Frequenzen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
    • Handle: RePEc:ces:ifosdt:v:62:y:2009:i:21:p:22-33
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    Cited by:

    1. Kai Carstensen & Steffen Henzel & Johannes Mayr & Klaus Wohlrabe, 2009. "IFOCAST: Methoden der ifo-Kurzfristprognose," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(23), pages 15-28, December.
    2. Klaus Wohlrabe, 2011. "Konstruktion von Indikatoren zur Analyse der wirtschaftlichen Aktivität in den Dienstleistungsbereichen," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 55, July.
    3. Christian Seiler & Klaus Wohlrabe, 2013. "Das ifo Geschäftsklima und die deutsche Konjunktur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.
    4. Anna Billharz & Steffen Elstner & Marcus Jüppner, 2012. "Methoden der ifo Kurzfristprognose am Beispiel der Ausrüstungsinvestitionen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(21), pages 24-33, November.
    5. Klaus Wohlrabe, 2012. "Prognose des Dienstleistungssektors in Deutschland," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(01), pages 31-39, January.

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    More about this item

    Keywords

    Prognose; Zeitreihenanalyse; Prognoseverfahren; VAR-Modell; Deutschland; MIDAS-Modell;
    All these keywords.

    JEL classification:

    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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