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Unpredictability and the Foundations of Economic Forecasting

Author

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  • David F. Hendry
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," Econometric Society 2004 Australasian Meetings 27, Econometric Society.
    • Handle: RePEc:ecm:ausm04:27
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    References listed on IDEAS

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    1. 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. WAN, Shui-Ki & WANG, Shin-Huei & WOO, Chi-Keung, 2012. "Total tourist arrival forecast: aggregation vs. disaggregation," LIDAM Discussion Papers CORE 2012039, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    3. Duo Qin & Marie Anne Cagas & Geoffrey Ducanes & Nedelyn Magtibay-Ramos & Pilipinas Quising, 2006. "Forecasting Inflation and GDP growth: Comparison of Automatic Leading Indicator (ALI) Method with Macro Econometric Structural Models (MESMs)," Working Papers 554, Queen Mary University of London, School of Economics and Finance.
    4. Duo Qin & Marie Anne Cagas & Geoffrey Ducanes & Nedelyn Magtibay-Ramos & Pilipinas Quising, 2007. "Automatic Leading Indicators (ALIs) versus Macro Econometric Structural Models (MESMs): Comparison of Inflation and GDP growth Forecasting," EcoMod2007 23900072, EcoMod.
    5. Hendry, David & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
    6. J. M. Kargbo, 2007. "Forecasting agricultural exports and imports in South Africa," Applied Economics, Taylor & Francis Journals, vol. 39(16), pages 2069-2084.
    7. 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.
    8. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.

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    More about this item

    Keywords

    Forecasting; Unpredictability;

    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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