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| Frees 교차-단면 의존성 검정 (Frees Cross-Sectional Dependence Test)× | 패널 데이터 고정 효과 모형× | Pesaran CD 검정: 패널 데이터의 횡단면 의존성 진단× | |
|---|---|---|---|
| 분야 | 계량경제학 | 계량경제학 | 계량경제학 |
| 계열≠ | Hypothesis test | Regression model | Hypothesis test |
| 기원 연도≠ | 1995 | 2014 | 2021 |
| 창시자≠ | Edward Frees | Hsiao (textbook treatment); within transformation of panel data | M. Hashem Pesaran |
| 유형≠ | Non-parametric panel diagnostic test | Panel data regression | Non-parametric diagnostic test |
| 원전≠ | Frees, 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 ↗ |
| 별칭 | 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 |
| 관련≠ | 3 | 5 | 3 |
| 요약≠ | 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. |
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