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Some forecasting principles from the M4 competition

Author

Listed:
  • Jennifer L. Castle

    (Magdelen College, University of Oxford)

  • Jurgen A. Doornik

    (Nuffield College, University of Oxford)

  • David Hendry

    (Nuffield College, University of Oxford)

Abstract
Economic forecasting is difficult, largely because of the many sources of nonstationarity. The M4 competition aims to improve the practice of economic forecasting by providing a large data set on which the efficacy of forecasting methods can be evaluated. We consider the general principles that seem to be the foundation for successful forecasting, and show how these are relevant for methods that do well in M4. We establish some general properties of the M4 data set, which we use to improve the basic benchmark methods, as well as the Card method that we created for our submission to the M4 competition. A data generation process is proposed that captures the salient features of the annual data in M4.

Suggested Citation

  • Jennifer L. Castle & Jurgen A. Doornik & David Hendry, 2019. "Some forecasting principles from the M4 competition," Economics Papers 2019-W01, Economics Group, Nuffield College, University of Oxford.
  • Handle: RePEc:nuf:econwp:1901
    as

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    File URL: https://www.nuffield.ox.ac.uk/economics/Papers/2019/2019W01_M4_forecasts.pdf
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2022. "Short-term forecasting of the coronavirus pandemic," International Journal of Forecasting, Elsevier, vol. 38(2), pages 453-466.
    2. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Short-term forecasting of the Coronavirus Pandemic - 2020-04-27," Economics Papers 2020-W06, Economics Group, Nuffield College, University of Oxford.
    3. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2020. "Card forecasts for M4," International Journal of Forecasting, Elsevier, vol. 36(1), pages 129-134.

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    More about this item

    Keywords

    Automatic forecasting; Calibration; Prediction intervals; Regression; M4; Seasonality; Software; Time series; Unit roots;
    All these keywords.

    JEL classification:

    • M4 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting

    NEP fields

    This paper has been announced in the following NEP Reports:

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