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| 그랜저 인과성 검정× | Kónya 부트스트랩 패널 Granger 인과관계 검정× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열≠ | Regression model | Hypothesis test |
| 기원 연도≠ | 1969 | 2006 |
| 창시자≠ | Clive W. J. Granger | László Kónya |
| 유형≠ | Time-series predictive causality test | Non-parametric bootstrap hypothesis test |
| 원전≠ | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗ | Kónya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978–992. DOI ↗ |
| 별칭 | Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi | Bootstrap Panel Causality Test, Kónya Panel Granger Causality, SUR-Based Bootstrap Causality, Kónya Önyükleme Nedensellik Testi |
| 관련≠ | 5 | 3 |
| 요약≠ | The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause. | Introduced by László Kónya in 2006, this method tests Granger causality in heterogeneous panels by estimating a Seemingly Unrelated Regressions (SUR) system and deriving country-specific critical values through bootstrapping. Unlike pooled panel tests, it delivers a separate causality verdict for each cross-section, making it particularly valuable in applied macroeconomics and international economics when panel units are expected to behave differently. |
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