Comparing Predictive Accuracy
National Bureau of Economic Research · University of Pennsylvania
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Abstract
AbstractWe propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss of function need not be quadratic and need not even be symmetric), and forecast errors can be non-Gaussian, nonzero mean, serially correlated, and contemporaneously correlated. Asymptotic and exact finite-sample tests are proposed, evaluated, and illustrated.KEY WORDS: Economic loss functionExchange ratesForecast evaluationForecastingNonparametric testsSign test
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Keywords
- Contrast (vision)
- Quadratic equation
- Null hypothesis
- Gaussian
- Null (SQL)
- Mathematics
- Statistics
- Function (biology)
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