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Robust Approaches to Forecasting

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  • Jennifer Castle
  • David Hendry
  • Michael P. Clements

Abstract

We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models.� Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift.� We derive the resulting forecast biases and error variances, and indicate when the methods are likely to perform well.� The robust methods are applied to forecasting US GDP using autoregressive models, and also to autoregressive models with factors extracted from a large dataset of macroeconomic variables.� We consider forecasting performance over the Great Recession, and over an earlier more quiescent period.

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Bibliographic Info

Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 697.

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Date of creation: 30 Jan 2014
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Handle: RePEc:oxf:wpaper:697

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Related research

Keywords: Robust forecasts; Smoothed Forecasting devices; Factor models; GDP forecasts; Location shifts;

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References

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  15. Jennifer Castle & David Hendry & Nicholas W.P. Fawcett, 2008. "Forecasting with Equilibrium-correction Models during Structural Breaks," Economics Series Working Papers 408, University of Oxford, Department of Economics.
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  17. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2012. "Model selection when there are multiple breaks," Journal of Econometrics, Elsevier, vol. 169(2), pages 239-246.
  18. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
  19. Michael P. Clements & Ana Beatriz Galvão, 2013. "Real‐Time Forecasting Of Inflation And Output Growth With Autoregressive Models In The Presence Of Data Revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 458-477, 04.
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Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. In all probability, economic forecasts are probably wrong
    by David F Hendry, Director, Economic Modelling, The Institute for New Economic Thinking at the Oxford Martin School at University of Oxford in The Conversation on 2014-07-18 12:06:35

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