Сравнение на методи

	Тест на Frees за кръстосана зависимост при панелни данни	Стандартни грешки на Дрискол-Краай	Модел с фиксирани ефекти за панелни данни
Област	Иконометрия	Иконометрия	Иконометрия
Семейство	Hypothesis test	Regression model	Regression model
Година на възникване	1995	1998	2014
Създател	Edward Frees	John Driscoll & Aart Kraay	Hsiao (textbook treatment); within transformation of panel data
Тип	Non-parametric panel diagnostic test	Nonparametric heteroskedasticity- and autocorrelation-consistent (HAC) covariance estimator for panel data	Panel data regression
Основополагащ източник	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.	Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press.
Други названия	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	fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Свързани	3	2	5
Резюме	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 Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).