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Unpredictability and the Foundations of Economic Forecasting

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  • David F. Hendry

    () (Economics Department, University of Oxford)

Abstract

We revisit the concept of unpredictability to explore its implications for forecasting strategies in a non-stationary world subject to structural breaks, where model and mechanism differ. Six aspects of the role of unpredictability are distinguished, compounding the four additional mistakes most likely in estimated forecasting models. Structural breaks, rather than limited information, are the key problem, exacerbated by conflicting requirements on forecast-error corrections. We consider model transformations and corrections to reduce forecast-error biases, as usual at some cost in increased forecast-error variances. The analysis is illustrated by an empirical application to M1 in the UK.

Suggested Citation

  • David F. Hendry, 2004. "Unpredictability and the Foundations of Economic Forecasting," Economics Papers 2004-W15, Economics Group, Nuffield College, University of Oxford.
  • Handle: RePEc:nuf:econwp:0415
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    File URL: http://www.nuff.ox.ac.uk/economics/papers/2004/w15/ForcBasis.pdf
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    References listed on IDEAS

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    3. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
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    6. Hendry, David F. & Ericsson, Neil R., 1991. "Modeling the demand for narrow money in the United Kingdom and the United States," European Economic Review, Elsevier, vol. 35(4), pages 833-881, May.
    7. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, May.
    8. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    9. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
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    Cited by:

    1. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, Elsevier.
    2. Hendry, David F & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
    3. J. M. Kargbo, 2007. "Forecasting agricultural exports and imports in South Africa," Applied Economics, Taylor & Francis Journals, vol. 39(16), pages 2069-2084.
    4. Qin, Duo & Cagas, Marie Anne & Ducanes, Geoffrey & Magtibay-Ramos, Nedelyn & Quising, Pilipinas, 2008. "Automatic leading indicators versus macroeconometric structural models: A comparison of inflation and GDP growth forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 399-413.
    5. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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