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Freedom of Choice in Macroeconomic Forecasting

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Author Info

  • Nikolay Robinzonov
  • Klaus Wohlrabe

Abstract

Different studies provide a surprisingly large variety of controversial conclusions about the forecasting power of an indicator, even when it is supposed to forecast the same time series. In this study, we aim to provide a thorough overview of linear forecasting techniques and draw conclusions useful for the identification of the predictive relationship between leading indicators and time series. In a case study for Germany, we forecast two possible representations of industrial production. Further on we consider a large variety of time-varying specifications. In a horse race with nine leading indicators plus an AR benchmark model, we demonstrate the variance 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 indicator proved to have better predicting power compared with another. Nevertheless, the freedom of choice can be useful to identify robust leading indicators. (JEL codes: C52, C53, E37) Copyright The Author 2009. Published by Oxford University Press on behalf of Ifo Institute for Economic Research, Munich. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

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Bibliographic Info

Article provided by CESifo in its journal CESifo Economic Studies.

Volume (Year): 56 (2010)
Issue (Month): 2 (June)
Pages: 192-220

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Handle: RePEc:oup:cesifo:v:56:y:2010:i:2:p:192-220

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Citations

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Cited by:
  1. Katja Rietzler & Sabine Stephan, 2012. "Monthly recession predictions in real time: A density forecast approach for German industrial production," IMK Working Paper 94-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
  2. Robert Lehmann & Antje Weyh, 2014. "Forecasting employment in Europe: Are survey results helpful?," Ifo Working Paper Series Ifo Working Paper No. 182, Ifo Institute for Economic Research at the University of Munich.
  3. Klaus Wohlrabe, 2011. "Konstruktion von Indikatoren zur Analyse der wirtschaftlichen Aktivität in den Dienstleistungsbereichen," ifo Forschungsberichte, Ifo Institute for Economic Research at the University of Munich, number 55, June.
  4. Christian Seiler, 2012. "On the Robustness of the Balance Statistics with respect to Nonresponse," Ifo Working Paper Series Ifo Working Paper No. 126, Ifo Institute for Economic Research at the University of Munich.
  5. Klaus Wohlrabe, 2012. "Prognose des Dienstleistungssektors in Deutschland," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 65(01), pages 31-39, 01.
  6. Anna Scharschmidt & Klaus Wohlrabe, 2011. "Sektorale Prognosen im Verarbeitenden Gewerbe," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 64(22), pages 27-35, November.
  7. Klaus Wohlrabe, 2009. "Makroökonomische Prognosen mit gemischten Frequenzen," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
  8. Anna Billharz & Steffen Elstner & Marcus Jüppner, 2012. "Methoden der ifo Kurzfristprognose am Beispiel der Ausrüstungsinvestitionen," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 65(21), pages 24-33, November.
  9. Robert Lehmann & Klaus Wohlrabe, 2012. "Die Prognose des Bruttoinlandsprodukts auf regionaler Ebene," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 65(21), pages 17-23, November.
  10. Christian Seiler & Klaus Wohlrabe, 2013. "Das ifo Geschäftsklima und die deutsche Konjunktur," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.
  11. Christian Seiler, 2013. "Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, Ifo Institute for Economic Research at the University of Munich, number 52.
  12. Katja Drechsel & Rolf Scheufele, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10, Halle Institute for Economic Research.
  13. Robert Lehmann & Klaus Wohlrabe, 2013. "Sektorale Prognosen und deren Machbarkeit auf regionaler Ebene – Das Beispiel Sachsen," ifo Dresden berichtet, Ifo Institute for Economic Research at the University of Munich, vol. 20(04), pages 22-29, 08.

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