Сравнение методов

	Стандартные ошибки Driscoll-Kraay	Стандартные ошибки HAC по Ньюи-Уэсту
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1998	1987
Автор метода	John Driscoll & Aart Kraay	Whitney Newey & Kenneth West
Тип	Nonparametric heteroskedasticity- and autocorrelation-consistent (HAC) covariance estimator for panel data	Covariance matrix estimator
Основополагающий источник	Driscoll, J. C., & Kraay, A. C. (1998). Consistent covariance matrix estimation with spatially dependent panel data. Review of Economics and Statistics, 80(4), 549–560.	Newey, W. K., & West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3), 703–708.
Другие названия	DK Standard Errors, Driscoll-Kraay Covariance Estimator, Spatial-Temporal HAC Standard Errors, Driscoll-Kraay Standart Hatalar	HAC standard errors, Heteroskedasticity and Autocorrelation Consistent covariance, Bartlett kernel HAC estimator, HAC düzeltmeli standart hatalar
Связанные	2	1
Сводка	Driscoll-Kraay standard errors provide a nonparametric, heteroskedasticity- and autocorrelation-consistent (HAC) covariance estimator for balanced and unbalanced panel datasets. Introduced by Driscoll and Kraay in 1998, the method corrects inference when residuals exhibit cross-sectional dependence, serial autocorrelation, and heteroskedasticity simultaneously—problems common in macroeconomic and international finance panels where units such as countries or industries share common shocks.	Newey-West HAC standard errors, introduced by Whitney Newey and Kenneth West in 1987, provide a covariance matrix estimator for OLS regression that remains valid under both heteroskedasticity and serial autocorrelation of unknown form. They are the standard tool for correcting inference in time-series and panel regression when residuals are not i.i.d., requiring no specification of the error structure beyond choosing a bandwidth parameter.