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Ujian Kebergantungan Keratan Rentas Bebas untuk Data Panel×Ralat Piawai Driscoll-Kraay×
BidangEkonometrikEkonometrik
KeluargaHypothesis testRegression model
Tahun asal19951998
PengasasEdward FreesJohn Driscoll & Aart Kraay
JenisNon-parametric panel diagnostic testNonparametric heteroskedasticity- and autocorrelation-consistent (HAC) covariance estimator for panel data
Sumber perintisFrees, E. W. (1995). Assessing cross-sectional correlation in panel data. Journal of Econometrics, 69(2), 393–414. DOI ↗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. DOI ↗
AliasFrees CD Test, Frees Q-statistic Test, Cross-Sectional Dependence Test (Frees), Frees Bağımlılık TestiDK Standard Errors, Driscoll-Kraay Covariance Estimator, Spatial-Temporal HAC Standard Errors, Driscoll-Kraay Standart Hatalar
Berkaitan32
RingkasanThe Frees test, introduced by Edward Frees in 1995, is a non-parametric diagnostic procedure for detecting cross-sectional dependence in panel data. It is designed for settings where N (number of units) is large and T (time periods) is moderate, making it a standard pre-estimation check before applying panel regression methods that assume cross-sectional independence. Applied economists and social scientists routinely use it to verify whether units in the panel share common shocks or spatial linkages.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.
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ScholarGateBandingkan kaedah: Frees Test · Driscoll-Kraay SE. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare