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Ifo Short-Term Forecasting Methods Illustrated Using Investment in Equipment

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Listed:
  • Anna Billharz
  • Steffen Elstner
  • Marcus Jüppner

Abstract

Business cycle forecasts are a key reference and basis for argumentation in corporate and state planning. Using investment in equipment as an example, this article shows the approach to forecasting a demand component of German GDP. The forecast covers both the current and the forthcoming year and is conducted in two steps. Firstly the short-term forecast is made for the current and forthcoming quarter. It is characterized by the fact that information in the form of indicators is already available for this period. The remaining period is forecast using econometric structuring models, whereby dynamic characteristics of the time series concerned and the various reference time series are updated.

Suggested Citation

  • Anna Billharz & Steffen Elstner & Marcus Jüppner, 2012. "Ifo Short-Term Forecasting Methods Illustrated Using Investment in Equipment," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(21), pages 24-33, November.
    • Handle: RePEc:ces:ifosdt:v:65:y:2012:i:21:p:24-33
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    References listed on IDEAS

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    1. Carstensen Kai & Wohlrabe Klaus & Ziegler Christina, 2011. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 82-106, February.
    2. Daniel Detzer & Christian R. Proaño & Katja Rietzler & Sven Schreiber & Thomas Theobald & Sabine Stephan, 2012. "Verfahren der konjunkturellen Wendepunktbestimmung unter Berücksichtigung der Echtzeit-Problematik," IMK Studies 27-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    3. Oliver Hülsewig & Johannes Mayr & Dirk Ulbricht, 2007. "On the evaluation of VAR forecasts," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 60(07), pages 19-25, April.
    4. Steffen Elstner & Christian Grimme & Thomas Siemsen, 2010. "The largest expanding markets for German exports are in Asia and Eastern Europe," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 63(16), pages 22-25, August.
    5. Schumacher, Christian & Loose, Brigitte & Langmantel, Erich & Gottschalk, Jan & Fritsche, Ulrich & Döpke, Jörg, 1999. "Indikatoren zur Prognose der Investitionen in Deutschland," Kiel Working Papers 906, Kiel Institute for the World Economy (IfW Kiel).
    6. 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.
    7. Wolfgang Nierhaus & Jan-Egbert Sturm, 2003. "Methods of business cycle forecasting," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(04), pages 7-23, February.
    8. Klaus Wohlrabe, 2009. "Macroeconomic forecasting with mixed frequencies," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
    9. Kai Carstensen & Steffen Henzel & Johannes Mayr & Klaus Wohlrabe, 2009. "IFOCAST: Methods of the Ifo short-term forecast," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(23), pages 15-28, December.
    10. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo Group, vol. 56(2), pages 192-220, June.
    11. Steffen Henzel & Johannes Mayr, 2009. "The Virtues of VAR Forecast Pooling – A DSGE Model Based Monte Carlo Study," ifo Working Paper Series 65, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
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    Cited by:

    1. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    2. Isabel Hanisch & Elisabeth Wieland & Timo Wollmershäuser, 2015. "The Development of German Investment Activity in a European Comparison – the Role of Price and Volume Effects," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(16), pages 39-50, August.
    3. 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.
    4. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72.
    5. Robert Lehmann & Andreas Sharik & Michael Weber, 2014. "Der Erklärungsgehalt der regionalen ifo-Indikatoren am Beispiel der Industrie- und Bauumsätze," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 21(04), pages 18-24, August.

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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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