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A Novel Approach to Forecasting After Large Forecast Errors

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  • Jennifer L. Castle
  • Jurgen A. Doornik
  • David F. Hendry

Abstract

A sequence of increasingly large same‐sign 1‐step‐ahead forecast errors are most likely due to a sudden unexpected shift. Large forecast errors can be expensive, but also contain valuable information. Impulse indicators acting as intercept corrections to set forecasts back on track can be quickly tested for replacing outliers, a location shift or broken trend, greatly improving forecast accuracy. The analysis is applied to forecasting the UK's annual consumer price inflation which rose rapidly from mid‐2021 to over 9% in 2022 after a series of essentially unpredictable shocks led to large forecast errors by the Bank of England.

Suggested Citation

  • Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2026. "A Novel Approach to Forecasting After Large Forecast Errors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(2), pages 837-849, March.
    • Handle: RePEc:wly:jforec:v:45:y:2026:i:2:p:837-849
    DOI: 10.1002/for.70062
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    References listed on IDEAS

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    1. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
    2. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, Enero-Abr.
    3. Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
    4. Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-1310, November.
    5. Nikolaos Giannellis & Stephen G. Hall & Georgios P. Kouretas & George S. Tavlas & Yongli Wang, 2025. "Policymaking in Periods of Structural Changes and Structural Breaks: Rolling Windows Revisited," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(3), pages 851-855, April.
    6. Hendry, David F. & Johansen, Søren, 2015. "Model Discovery And Trygve Haavelmo’S Legacy," Econometric Theory, Cambridge University Press, vol. 31(1), pages 93-114, February.
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