विधियों की तुलना करें

	पैनल डेटा के लिए फ्रीज़ क्रॉस-सेक्शनल डिपेंडेंस टेस्ट	ड्रिस्कॉल-क्रे (Driscoll-Kraay) मानक त्रुटियाँ	पेसारन सीडी टेस्ट: पैनल डेटा के लिए क्रॉस-सेक्शनल डिपेंडेंस डायग्नोस्टिक
क्षेत्र	अर्थमिति	अर्थमिति	अर्थमिति
परिवार	Hypothesis test	Regression model	Hypothesis test
उद्भव वर्ष	1995	1998	2021
प्रवर्तक	Edward Frees	John Driscoll & Aart Kraay	M. Hashem Pesaran
प्रकार	Non-parametric panel diagnostic test	Nonparametric heteroskedasticity- and autocorrelation-consistent (HAC) covariance estimator for panel data	Non-parametric diagnostic test
मौलिक स्रोत	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.
उपनाम	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
संबंधित	3	2	3
सारांश	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.