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Driscoll-Kraayovy standardní chyby×Robustní standardní chyby Newey-West HAC×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku19981987
TvůrceJohn Driscoll & Aart KraayWhitney Newey & Kenneth West
TypNonparametric heteroskedasticity- and autocorrelation-consistent (HAC) covariance estimator for panel dataCovariance matrix estimator
Původní zdrojDriscoll, J. C., & Kraay, A. C. (1998). Consistent covariance matrix estimation with spatially dependent panel data. Review of Economics and Statistics, 80(4), 549–560. DOI ↗Newey, W. K., & West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3), 703–708. DOI ↗
Další názvyDK Standard Errors, Driscoll-Kraay Covariance Estimator, Spatial-Temporal HAC Standard Errors, Driscoll-Kraay Standart HatalarHAC standard errors, Heteroskedasticity and Autocorrelation Consistent covariance, Bartlett kernel HAC estimator, HAC düzeltmeli standart hatalar
Příbuzné21
ShrnutíDriscoll-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.
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ScholarGatePorovnat metody: Driscoll-Kraay SE · Newey-West HAC. Získáno 2026-06-20 z https://scholargate.app/cs/compare