Salīdzināt metodes

	Frees šķērsgriezuma atkarības tests panelu datiem	Fiksēto efektu paneļa datu modelis	Pesaran CD Test
Nozare	Ekonometrija	Ekonometrija	Ekonometrija
Saime	Hypothesis test	Regression model	Hypothesis test
Izcelsmes gads	1995	2014	2021
Autors	Edward Frees	Hsiao (textbook treatment); within transformation of panel data	M. Hashem Pesaran
Tips	Non-parametric panel diagnostic test	Panel data regression	Non-parametric diagnostic test
Pirmavots	Frees, E. W. (1995). Assessing cross-sectional correlation in panel data. Journal of Econometrics, 69(2), 393–414.	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.
Citi nosaukumi	Frees CD Test, Frees Q-statistic Test, Cross-Sectional Dependence Test (Frees), Frees Bağımlılık Testi	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
Saistītās	3	5	3
Kopsavilkums	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.	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.