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Abstract

Sections 2.1 and 2.2 consider the evaluation of sequences of point forecasts in terms of the first- and second-moment properties of the forecast errors. Section 2.3 allows that there is at least one rival set of forecasts of the variable of interest, and asks which of the two is better, as well as whether even the less good of the two provides some useful information. In Section 2.4 we explicitly allow that the forecasts have been generated by models. At this point, the question becomes not which of the sets of forecasts is best, but which of the models generates more accurate forecasts, as judged by out-of-sample tests of predictive ability. Section 2.5 considers a number of issues that arise in the evaluation of forecasts from non-linear models.

Keywords

Forecast Error Conditional Expectation Forecast Accuracy Ordinary Little Square Estimator Point Forecast 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Michael P. Clements 2005

Authors and Affiliations

  • Michael P. Clements
    • 1
  1. 1.University of WarwickUK

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