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Forecasting qualities of the Ifo Business Climate Index - a look at recent studies

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  • Klaus Abberger
  • Klaus Wohlrabe

Abstract

The Ifo Business Climate is a closely ifo is a much considered indicator for the economic evolution in Germany. It is again and again the subject of scientific analyses in which the different qualities of the business climate are examined. At the centre of interest is often the use of the indicator for forecasting purposes. The German Council of Economic Experts, for example, devoted a section of its annual report for 2006/2007 to the Ifo Business Climate. This study by the Ifo Institute confirms the very good performance of the Ifo Business Climate Index as an early indicator for the business developments in manufacturing. The Munich experts have compared the leading-indicator properties of the Ifo Business Climate with the production index in manufacturing. The Ifo Business Climate has an average lead in the turning points of nearly two months and contains a considerably clear business-cycle signal, which is considerably stronger than the production index. For a business-cycle indicator, these are very positive characteristics. An additional advantage of the Ifo Index, is its timely publication. The Ifo survey results are published about four weeks before the production index. This gives the Ifo Business Climate a publication lead in addition to the calculated lead of two months.

Suggested Citation

  • Klaus Abberger & Klaus Wohlrabe, 2006. "Forecasting qualities of the Ifo Business Climate Index - a look at recent studies," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
    • Handle: RePEc:ces:ifosdt:v:59:y:2006:i:22:p:19-26
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    1. Schumacher, Christian & Breitung, Jörg, 2006. "Real-time forecasting of GDP based on a large factor model with monthly and quarterly data," Discussion Paper Series 1: Economic Studies 2006,33, Deutsche Bundesbank.
    2. Bénédicte Vidaillet & V. d'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    3. Fritsche Ulrich & Stephan Sabine, 2002. "Leading Indicators of German Business Cycles. An Assessment of Properties / Frühindikatoren der deutschen Konjunktur. Eine Beurteilung ihrer Eigenschaften," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(3), pages 289-315, June.
    4. Jan-Egbert Sturm & Timo Wollmershäuser (ed.), 2005. "Ifo Survey Data in Business Cycle and Monetary Policy Analysis," Contributions to Economics, Springer, number 978-3-7908-1605-1.
    5. Kholodilin Konstantin Arkadievich & Siliverstovs Boriss, 2006. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(3), pages 234-259, June.
    6. Jan Jacobs & Jan-Egbert Sturm, 2005. "Do Ifo Indicators Help Explain Revisions in German Industrial Production?," Contributions to Economics, in: Jan-Egbert Sturm & Timo Wollmershäuser (ed.), Ifo Survey Data in Business Cycle and Monetary Policy Analysis, pages 93-114, Springer.
    7. Dreger, Christian & Schumacher, Christian, 2002. "Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models?," Discussion Paper Series 26321, Hamburg Institute of International Economics.
    8. Stefan Mittnik & Peter Zadrozny, 2005. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly Ifo Business Conditions Data," Contributions to Economics, in: Jan-Egbert Sturm & Timo Wollmershäuser (ed.), Ifo Survey Data in Business Cycle and Monetary Policy Analysis, pages 19-48, Springer.
    9. Döpke, Jörg, 1999. "Predicting Germany's recessions with leading indicators: Evidence from probit models," Kiel Working Papers 944, Kiel Institute for the World Economy (IfW Kiel).
    10. Claveria, Oscar & Pons, Ernest & Ramos, Raul, 2007. "Business and consumer expectations and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 47-69.
    11. Klaus Abberger, 2006. "Ifo Business Climate and the production index in manufacturing," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(21), pages 42-45, November.
    12. Christian Dreger & Christian Schumacher, 2005. "Out-of-sample Performance of Leading Indicators for the German Business Cycle: Single vs. Combined Forecasts," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(1), pages 71-87.
    13. Erich Langmantel, 1999. "Das ifo Geschäftsklima als Indikator für die Prognose des Bruttoinlandsprodukts," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 52(16-17), pages 16-21, October.
    14. Wolfgang Nierhaus, 1999. "Aus dem Instrumentenkasten der Konjunkturanalyse : Veränderungen im Vergleich," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 52(27), pages 11-19, October.
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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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