On Not Evaluating Economic Models by Forecast Outcomes
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.
|Date of creation:||01 Feb 2011|
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