Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics

B-Tier
Journal: Journal of Applied Econometrics
Year: 2020
Volume: 35
Issue: 4
Pages: 391-409

Authors (2)

Score contribution per author:

1.005 = (α=2.01 / 2 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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.

Technical Details

RePEc Handle
repec:wly:japmet:v:35:y:2020:i:4:p:391-409
Journal Field
Econometrics
Author Count
2
Added to Database
2026-01-25