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On Not Evaluating Economic Models by Forecast Outcomes

Author

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  • Jennifer Castle
  • David Hendry

Abstract

Even in scientific disciplines, forecast failures occur. Four possible states of nature (a model is good or bad, and it forecasts well or badly) are examined using a forecast-error taxonomy, which traces the many possible sources of forecast errors. This analysis shows that a valid model can forecast badly, and a poor model can forecast successfully. Delineating the main causes of forecast failure reveals transformations that can correct failure without altering the 'quality' of the model in use. We conclude that judging a model by the accuracy of its forecasts is more like fools' gold than a gold standard.

Suggested Citation

  • Jennifer Castle & David Hendry, 2011. "On Not Evaluating Economic Models by Forecast Outcomes," Economics Series Working Papers 538, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:538
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    File URL: http://www.economics.ox.ac.uk/materials/papers/4902/paper538.pdf
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    Cited by:

    1. Jennifer Castle & David Hendry, 2016. "Policy Analysis, Forediction, and Forecast Failure," Economics Series Working Papers 809, University of Oxford, Department of Economics.
    2. repec:gam:jecnmx:v:5:y:2017:i:3:p:39-:d:110547 is not listed on IDEAS

    More about this item

    Keywords

    Model evaluation; Forecast failure; Model selection;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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