Сравнение методов

	Стандартные ошибки Driscoll-Kraay	Модель с фиксированными эффектами для панельных данных	Тест Песарана CD: диагностика пространственной зависимости для панельных данных
Область	Эконометрика	Эконометрика	Эконометрика
Семейство	Regression model	Regression model	Hypothesis test
Год появления	1998	2014	2021
Автор метода	John Driscoll & Aart Kraay	Hsiao (textbook treatment); within transformation of panel data	M. Hashem Pesaran
Тип	Nonparametric heteroskedasticity- and autocorrelation-consistent (HAC) covariance estimator for panel data	Panel data regression	Non-parametric diagnostic test
Основополагающий источник	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.	Pesaran, M. H. (2021). General diagnostic tests for cross-sectional dependence in panels. Empirical Economics, 60(1), 13–50.
Другие названия	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	CD Test, Cross-Sectional Dependence Test, Pesaran General CD Test, Kesitsel Bağımlılık Testi
Связанные	2	5	3
Сводка	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).	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.