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	Giacomini-White-testet för villkorad prediktiv förmåga	Stegvis regression
Ämnesområde	Ekonometri	Statistik
Familj	Hypothesis test	Regression model
Ursprungsår	2006	1960
Upphovsperson	Raffaella Giacomini & Halbert White	M. A. Efroymson
Typ	Non-nested forecast comparison test	Automated variable selection
Ursprungskälla	Giacomini, R., & White, H. (2006). Tests of conditional predictive ability. Econometrica, 74(6), 1545–1578.	Efroymson, M. A. (1960). Multiple regression analysis. In A. Ralston & H. S. Wilf (Eds.), Mathematical Methods for Digital Computers (pp. 191–203). Wiley.
Alias	GW Test, Conditional Predictive Ability Test, Giacomini-White CPA Test, Koşullu Tahmin Yeteneği Testi	stepwise selection, forward stepwise regression, backward stepwise regression, forward-backward selection
Närliggande	3	5
Sammanfattning	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.	Stepwise regression is an automated variable selection procedure for multiple linear regression that adds or removes predictor variables one at a time according to a statistical criterion, typically the F-statistic or a p-value threshold. The forward-selection algorithm was formally described by Efroymson (1960) and the bidirectional variant was popularised by Draper and Smith in their landmark 1966 text Applied Regression Analysis. Despite widespread historical use, the method is now widely critiqued, making its documentation essential in any canonical methods library.