Comparing Predictive Accuracy
Abstract
The authors 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 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.Download Info
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Bibliographic Info
Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 13 (1995)
Issue (Month): 3 (July)
Pages: 253-63
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Handle: RePEc:bes:jnlbes:v:13:y:1995:i:3:p:253-63
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Related research
Keywords:Other versions of this item:
- Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, . "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting Models; Simulation Methods
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