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Prognosegüte alternativer Früh Indikatoren für die Konjunktur in Deutschland / Forecasting Performance of Alternative Indicators for the German Economy

  • Benner Joachim

    ()

  • Meier Carsten-Patrick

    ()

    (Institut für Weltwirtschaft an der Universität Kiel, Deutsche Konjunktur, Düsternbrooker Weg 120, D-24105 Kiel. Tel.: ++49/+4 31/ 8 8141, Fax: +-M9/+4 31/8 8145 25, Germany)

Registered author(s):

    Analyses of the fit of forecasts should not only observe the forecast errors which are based on the estimation of the parameters but also those based on the uncertainty from selecting the specification of the forecasting model from the sample data. We argue that it is important to estimate the parameters and also the model selection recursively. In this paper we compare the forecasting ability of three important German business cycle indicators: the ifo business expectations, the ZEW business expectations and the „Earlybird“ Indicator published in „Wirtschaftswoche“. Our results show that the forecast errors are higher when using the more realistic recursive model selection instead of using the non-recursive specification. In certain cases the analysed business cycle indicators provide better forecasts than the naive forecast based on its own lagged values.

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    File URL: http://www.degruyter.com/view/j/jbnst.2004.224.issue-6/jbnst-2004-0602/jbnst-2004-0602.xml?format=INT
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    Article provided by De Gruyter in its journal Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik).

    Volume (Year): 224 (2004)
    Issue (Month): 6 (December)
    Pages: 639-652

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    Handle: RePEc:jns:jbstat:v:224:y:2004:i:6:p:639-652
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    1. Ulrich Fritsche, 2001. "Do Probit Models Help in Forecasting Turning Points in German Business Cycles?," Discussion Papers of DIW Berlin 241, DIW Berlin, German Institute for Economic Research.
    2. Franses, Philip Hans & Lucas, Andre, 1998. "Outlier Detection in Cointegration Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 459-68, October.
    3. Kilian, Lutz, 2001. "Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(3), pages 161-79, April.
    4. Ulrich Fritsche & Sabine Stephan, 2000. "Leading Indicators of German Business Cycles: An Assessment of Properties," Macroeconomics 0004005, EconWPA.
    5. Ulrich Fritsche, 1999. "Vorlaufeigenschaften von Ifo-Indikatoren für Westdeutschland," Discussion Papers of DIW Berlin 179, DIW Berlin, German Institute for Economic Research.
    6. Brüggemann, Ralf & Lütkepohl, Helmut, 2000. "Lag selection in subset VAR models with an application to a US monetary system," SFB 373 Discussion Papers 2000,37, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    8. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    9. Norbert Funke, 1997. "Predicting recessions: Some evidence for Germany," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 133(1), pages 90-102, March.
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