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VAR-Prognose-Pooling : ein Ansatz zur Verbesserung der Informationsgrundlage der ifo Dresden Konjunkturprognosen

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  • Gerit Vogt

Abstract

Seit einigen Jahren werden von der Dresdner Niederlassung des ifo Instituts im halbjährlichen Rhythmus Prognosen zur gesamtwirtschaftlichen Entwicklung in Sachsen und Ostdeutschland erstellt. Das Bruttoinlandsprodukt (BIP), als wichtigste Konjunktur- und Prognosevariable, wird dabei entstehungsseitig aus der in den einzelnen Wirtschaftsbereichen erwarteten Bruttowertschöpfung berechnet. In diesem Beitrag wird ein Ansatz vorgestellt, der die Informationsgrundlage der ifo Dresden-Konjunkturprognosen verbessern soll. Er basiert auf der Kombination von Prognosen, die mit sparsam spezifizierten vektorautoregressiven Modellen (VAR-Modellen) generiert werden. Der Ansatz wird anhand der vierteljährlichen BIP-Daten vorgestellt, die jüngst vom ifo Institut für den Freistaat Sachsen vorgelegt wurden.

Suggested Citation

  • Gerit Vogt, 2010. "VAR-Prognose-Pooling : ein Ansatz zur Verbesserung der Informationsgrundlage der ifo Dresden Konjunkturprognosen," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(02), pages .32-40, April.
    • Handle: RePEc:ces:ifodre:v:17:y:2010:i:02:p:s.32-40
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    References listed on IDEAS

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    1. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    2. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    3. Johannes Mayr & Dirk Ulbricht, 2007. "VAR Model Averaging for Multi-Step Forecasting," ifo Working Paper Series 48, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
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    Cited by:

    1. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    2. Wenzel, Lars, 2013. "Forecasting regional growth in Germany: A panel approach using business survey data," HWWI Research Papers 133, Hamburg Institute of International Economics (HWWI).
    3. Robert Lehmann & Klaus Wohlrabe, 2012. "Forecast of Gross Domestic Product at a Regional Level," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(21), pages 17-23, November.
    4. Christian Seiler & Klaus Wohlrabe, 2013. "The Ifo Business Climate and the German Economy," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.

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    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets

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