Tests for relative predictive accuracy have become a widespread addendum to forecast comparisons. Many empirical research reports conclude that the difference between the entertained forecasting models is 'insignificant'. This paper collects arguments that cast doubt on the usefulness of relative predictive accuracy tests. The main point is not that test power is too low but that their application is conceptually mistaken. The features are highlighted by means of some Monte Carlo experiments for simple time-series decision problems.
information criteria forecasting hypothesis testing