Linganisha mbinu

	Frees Cross-Sectional Dependence Test for Panel Data	Hitilafu Sanifu za Driscoll-Kraay	Jaribio la Pesaran CD: Utambuzi wa Utegemezi wa Kimitambuka kwa Data ya Paneli
Nyanja	Ekonometriki	Ekonometriki	Ekonometriki
Familia	Hypothesis test	Regression model	Hypothesis test
Mwaka wa asili	1995	1998	2021
Mwanzilishi	Edward Frees	John Driscoll & Aart Kraay	M. Hashem Pesaran
Aina	Non-parametric panel diagnostic test	Nonparametric heteroskedasticity- and autocorrelation-consistent (HAC) covariance estimator for panel data	Non-parametric diagnostic test
Chanzo asilia	Frees, E. W. (1995). Assessing cross-sectional correlation in panel data. Journal of Econometrics, 69(2), 393–414.	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.	Pesaran, M. H. (2021). General diagnostic tests for cross-sectional dependence in panels. Empirical Economics, 60(1), 13–50.
Majina mbadala	Frees CD Test, Frees Q-statistic Test, Cross-Sectional Dependence Test (Frees), Frees Bağımlılık Testi	DK Standard Errors, Driscoll-Kraay Covariance Estimator, Spatial-Temporal HAC Standard Errors, Driscoll-Kraay Standart Hatalar	CD Test, Cross-Sectional Dependence Test, Pesaran General CD Test, Kesitsel Bağımlılık Testi
Zinazohusiana	3	2	3
Muhtasari	The 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.	The Pesaran CD test is a general diagnostic procedure for detecting cross-sectional dependence in panel data models. Developed by M. Hashem Pesaran (2021), it is applicable to both balanced and unbalanced panels with large N and T, and retains validity under heterogeneous slope coefficients. The test is widely adopted in empirical economics, finance, and political economy as a prerequisite check before selecting appropriate estimators or unit-root tests for panel datasets.