השוואת שיטות

	מבחן פריס לתלות רוחבית בנתוני פאנל	מודל האפקטים הקבועים לנתוני פאנל	מבחן Pesaran CD: אבחון תלות חתך-ממדי עבור נתוני פאנל
תחום	אקונומטריקה	אקונומטריקה	אקונומטריקה
משפחה	Hypothesis test	Regression model	Hypothesis test
שנת המקור	1995	2014	2021
הוגה השיטה	Edward Frees	Hsiao (textbook treatment); within transformation of panel data	M. Hashem Pesaran
סוג	Non-parametric panel diagnostic test	Panel data regression	Non-parametric diagnostic test
מקור מכונן	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.
כינויים	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
קשורות	3	5	3
תקציר	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.