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Freedom of Choice in Macroeconomic Forecasting: An Illustration with German Industrial Production and Linear Models

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  • Nikolay Robinzonov
  • Klaus Wohlrabe

    ()

Abstract

Different studies provide surprisingly a large variety of controversial conclusions aboutthe forecasting power of an indicator, even when it is supposed to forecast the sametime series. In this study we aim to provide a thorough overview of linear forecastingtechniques and draw conclusions useful for the identification of the predictive relationshipbetween leading indicators and time series. In a case study for Germany we forecastfour possible representations of industrial production. Further on we consider alarge variety of time-varying specifications: ex post vs. ex ante, rolling vs. recursive andmodel specifications such as restricted vs. unrestricted, AIC vs. BIC vs. OSC, direct vs.indirect. In a horse race with nine leading indicators plus benchmark we demonstrate thevariance of assessment across target variables and forecasting settings (50 per horizon).We show that it is nearly always possible to find situations in which one indicatorproved to have better predicting power compared to another.

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Bibliographic Info

Paper provided by Ifo Institute for Economic Research at the University of Munich in its series Ifo Working Paper Series with number Ifo Working Paper No. 57.

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Date of creation: 2008
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Handle: RePEc:ces:ifowps:_57

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Keywords: Forecasting competition; leading indicators; model selection;

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References

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Cited by:
  1. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Nowcasting Business Cycles Using Toll Data," IZA Discussion Papers 5522, Institute for the Study of Labor (IZA).
  2. Gerit Vogt, 2009. "Konjunkturprognose in Deutschland. Ein Beitrag zur Prognose der gesamtwirtschaftlichen Entwicklung auf Bundes- und Länderebene," ifo Beiträge zur Wirtschaftsforschung, Ifo Institute for Economic Research at the University of Munich, Ifo Institute for Economic Research at the University of Munich, number 36, 8.

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