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Test niezależności przekrojowej Freesa dla danych panelowych×Model efektów stałych dla danych panelowych×Test Pesaran CD: Diagnostyka zależności przekrojowej dla danych panelowych×
DziedzinaEkonometriaEkonometriaEkonometria
RodzinaHypothesis testRegression modelHypothesis test
Rok powstania199520142021
TwórcaEdward FreesHsiao (textbook treatment); within transformation of panel dataM. Hashem Pesaran
TypNon-parametric panel diagnostic testPanel data regressionNon-parametric diagnostic test
Źródło pierwotneFrees, E. W. (1995). Assessing cross-sectional correlation in panel data. Journal of Econometrics, 69(2), 393–414. DOI ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗Pesaran, M. H. (2021). General diagnostic tests for cross-sectional dependence in panels. Empirical Economics, 60(1), 13–50. DOI ↗
Inne nazwyFrees CD Test, Frees Q-statistic Test, Cross-Sectional Dependence Test (Frees), Frees Bağımlılık Testifixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler ModeliCD Test, Cross-Sectional Dependence Test, Pesaran General CD Test, Kesitsel Bağımlılık Testi
Pokrewne353
PodsumowanieThe 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.
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