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Treffgenauigkeit, Rationalität und Streuung von Konjunkturprognosen für Deutschland

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  • Ulrich Fritsche
  • Jörg Döpke

Abstract

Konjunkturprognostiker und deren prognostische Fähigkeiten standen schon oft im Kreuzfeuer der öffentlichen Kritik. Seit einiger Zeit mehren sich die Fragen über die Tauglichkeit von Konjunkturprognosen. Da war vom "Blindflug der Forscher" zu lesen (vgl. Der Spiegel 2005), Feuilletonisten forderten "Entlasst die Experten" (vgl. FAZ 2005a) und auch Altbundeskanzler Gerhard Schröder hegte wenig Sympathie für "diese Art der Wissenschaft, die ihn an Meteorologie erinnere" (vgl. FAZ 2005b). Dass viele Wirtschaftsforschungsinstitute mit öffentlichen Geldern gefördert werden, steigert den Legitimationsdruck zusätzlich. Umso wichtiger ist es, die Debatte zu versachlichen und sich Grenzen, Möglichkeiten und Chancen der Konjunkturprognosen unter Verwendung nachprüfbarer Kriterien vor Augen zu führen.1 Der folgende Beitrag soll dazu beitragen. Dazu wird zunächst im Abschnitt 2 der Frage nachgegangen, welche erkenntnistheoretischen Probleme es grundsätzlich bei Prognosen gibt und was diese leisten können. Abschnitt 3 beschreibt den für die folgenden empirischen Untersuchungen verwendeten Datensatz. Im Abschnitt 4 geht es um die Treffgenauigkeit und Rationalität von Prognosen und im Abschnitt 5 soll geklärt werden, warum Prognosen differieren und welche Bestimmungsgründe es für Phasen hoher Divergenz bei den Prognosen geben könnte. Abschnitt 6 fasst die Ergebnisse zusammen.

Suggested Citation

  • Ulrich Fritsche & Jörg Döpke, 2006. "Treffgenauigkeit, Rationalität und Streuung von Konjunkturprognosen für Deutschland," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 75(2), pages 34-53.
    • Handle: RePEc:diw:diwvjh:75-2-3
    DOI: 10.3790/vjh.75.2.34
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    References listed on IDEAS

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    1. Keane, Michael P & Runkle, David E, 1990. "Testing the Rationality of Price Forecasts: New Evidence from Panel Data," American Economic Review, American Economic Association, vol. 80(4), pages 714-735, September.
    2. Bomberger, William A, 1996. "Disagreement as a Measure of Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(3), pages 381-392, August.
    3. Victor Zarnowitz & Louis A. Lambros, 1983. "Consensus and Uncertainty in Economic Prediction," NBER Working Papers 1171, National Bureau of Economic Research, Inc.
    4. Dopke, Jorg & Fritsche, Ulrich, 2006. "When do forecasters disagree? An assessment of German growth and inflation forecast dispersion," International Journal of Forecasting, Elsevier, vol. 22(1), pages 125-135.
    5. Holden, K & Peel, D A, 1990. "On Testing for Unbiasedness and Efficiency of Forecasts," The Manchester School of Economic & Social Studies, University of Manchester, vol. 58(2), pages 120-127, June.
    6. Gebhardt Kirschgässner & Marcel Savioz, 2001. "Monetary Policy and Forecasts for Real GDP Growth: An Empirical Investigation for the Federal Republic of Germany," German Economic Review, Verein für Socialpolitik, vol. 2(4), pages 339-365, November.
    7. Zarnowitz, Victor & Lambros, Louis A, 1987. "Consensus and Uncertainty in Economic Prediction," Journal of Political Economy, University of Chicago Press, vol. 95(3), pages 591-621, June.
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    Cited by:

    1. Ulrich Fritsche & Artur Tarassow, 2017. "Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014," IMK Studies 54-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    2. Alfred Steinherr, 2006. "80 Years of Business Cycle Studies at DIW Berlin: Editorial," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 75(2), pages 5-11.

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