Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics

Laura Coroneo · Fabrizio Iacone

51 citations0/0 files storedJournal of Applied Econometrics

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Forecasting Techniques and Applications Monetary Policy and Economic Impact Statistical Methods and Inference

Abstract

Summary We consider fixed‐smoothing asymptotics for the Diebold and Mariano ( Journal of Business and Economic Statistics , 1995, 13 (3), 253–263) test of predictive accuracy. We show that this approach delivers predictive accuracy tests that are correctly sized even when only a small number of out‐of‐sample observations is available. We apply the fixed‐smoothing asymptotics to the Diebold and Mariano test to evaluate the predictive accuracy of the Survey of Professional Forecasters (SPF) and of the European Central Bank Survey of Professional Forecasters (ECB SPF) against a simple random walk. Our results show that the predictive abilities of the SPF and of the ECB SPF were partially spurious.

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References

1994Comparing Predictive Accuracy 1995Comparing Predictive Accuracy 1994Automatic Lag Selection in Covariance Matrix Estimation 2006Approximately normal tests for equal predictive accuracy in nested models 1997Testing the equality of prediction mean squared errors 2006Tests of Conditional Predictive Ability 1996Asymptotic Inference about Predictive Ability 2001Tests of equal forecast accuracy and encompassing for nested models

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