Salīdzināt metodes

	Dībolda-Mariāno tests par prognožu precizitātes līdzvērtību	Giacomini-White kondicionālās prognozēšanas spējas tests
Nozare	Ekonometrija	Ekonometrija
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	1995	2006
Autors	Francis Diebold & Roberto Mariano	Raffaella Giacomini & Halbert White
Tips	Non-parametric forecast comparison test	Non-nested forecast comparison test
Pirmavots	Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263.	Giacomini, R., & White, H. (2006). Tests of conditional predictive ability. Econometrica, 74(6), 1545–1578.
Citi nosaukumi	DM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi	GW Test, Conditional Predictive Ability Test, Giacomini-White CPA Test, Koşullu Tahmin Yeteneği Testi
Saistītās	3	3
Kopsavilkums	The Diebold-Mariano (DM) test, introduced by Diebold and Mariano in 1995, is a widely used non-parametric procedure for formally comparing the predictive accuracy of two competing forecasting models. It evaluates whether the difference in forecast errors between two models is statistically significant, without requiring nested models or specific distributional assumptions about the forecasts, making it broadly applicable across economics, finance, and time-series analysis.	The Giacomini-White (GW) test, introduced by Raffaella Giacomini and Halbert White in 2006, evaluates whether two competing forecasting methods have equal conditional predictive ability given information available at the time of forecast. Unlike unconditional tests such as the Diebold-Mariano test, it asks whether one method systematically outperforms the other in specific economic or market conditions, making it especially useful for practitioners who need state-dependent forecast comparisons.