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An Open-model Forecast-error Taxonomy


  • David Hendry
  • Grayham E. Mizon


We develop forecast-error taxonomies when there are unmodeled variables, forecast 'off-line'. We establish three surprising results. Even when an open system is correctly specified in-sample with zero intercepts, despite known future values of strongly exogenous variables, changes in dynamics can induce forecast failure when they have non-zero means. The additional impact on forecast failure of incorrectly omitting such variables depends only on shifts in their means. With no such shifts, there is no reduction in forecast failure from forecasting unmodeled variables relative to omitting them in 1-step or multi-step forecasts. Simulation illustrations confirm these results.

Suggested Citation

  • David Hendry & Grayham E. Mizon, 2011. "An Open-model Forecast-error Taxonomy," Economics Series Working Papers 552, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:552

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    Forecasting; Forecast-error taxonomies; Location shifts; Open models;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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