방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 패널 그랜저 인과성 검정× | Granger 인과관계 검정× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1988–2012 | 1969 |
| 창시자≠ | Holtz-Eakin, Newey & Rosen (1988); Dumitrescu & Hurlin (2012) | Clive W. J. Granger |
| 유형≠ | Causality test | Causality test (F-test on VAR) |
| 원전≠ | Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. DOI ↗ | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. DOI ↗ |
| 별칭 | panel causality test, Dumitrescu-Hurlin test, heterogeneous panel causality, panel Granger test | Granger test, GC test, predictive causality test, Granger non-causality test |
| 관련 | 5 | 5 |
| 요약≠ | The Panel Granger Causality test examines whether past values of one variable help predict another variable across multiple cross-sectional units observed over time. It extends the classical Granger causality framework to panel data, accounting for cross-sectional heterogeneity and enabling more powerful inference by pooling information across units. | The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis. |
| ScholarGate데이터셋 ↗ |
|
|