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Zur Evaluierung von VAR-Prognosen

Listed author(s):
  • Oliver Hülsewig
  • Johannes Mayr
  • Dirk Ulbricht

In diesem Beitrag wird die Verwendung von VAR-Modellen für die Prognose des realen Bruttoinlandsprodukts in den Vereinigten Staaten analysiert. Den Ausgangspunkt bildet ein Basismodell, das neben dem realen BIP den Verbraucherpreisindex sowie einen kurzfristigen Geldmarktsatz enthält. Das Basismodell wird anschließend durch die Einbeziehung zusätzlicher makroökonomischer Variablen schrittweise erweitert. Die Prognosen der einzelnen Modelle, die als out-of-sample Prognosen generiert werden, werden für verschiedene Schätzzeiträume anhand unterschiedlicher Maße zur Überprüfung der Anpassungsgüte evaluiert. Es zeigt sich, dass die Prognosen der VAR-Modelle durchschnittlich schlechter als die eines univariaten AR(2)-Prozesses abschneiden. Die Qualität der Prognosen variiert jedoch stark in den betrachteten Schätzzeiträumen, so dass die VAR-Prognosen in einzelnen Perioden die AR(2)-Prognosen deutlich dominieren. Für die Erstellung von Prognosen erscheint es daher empfehlenswert zu sein, mehrere Modelle simultan zu betrachten.

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

Volume (Year): 60 (2007)
Issue (Month): 07 (04)
Pages: 19-25

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Handle: RePEc:ces:ifosdt:v:60:y:2007:i:07:p:19-25
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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.:

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  1. Ben S. Bernanke & Mark Gertler & Mark Watson, 1997. "Systematic Monetary Policy and the Effects of Oil Price Shocks," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 28(1), pages 91-157.
  2. Wolfgang Nierhaus & Jan-Egbert Sturm, 2003. "Methoden der Konjunkturprognose," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(04), pages 7-23, 02.
  3. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
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