On Not Evaluating Economic Models by Forecast Outcomes
AbstractEven 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.
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Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 538.
Date of creation: 01 Feb 2011
Date of revision:
Model evaluation; Forecast failure; Model selection;
Find related papers by 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-03-12 (All new papers)
- NEP-CBA-2011-03-12 (Central Banking)
- NEP-ECM-2011-03-12 (Econometrics)
- NEP-FOR-2011-03-12 (Forecasting)
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