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| Test di Causalità di Granger Robusto× | Test di causalità di Granger× | |
|---|---|---|
| Campo | Econometria | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2006 (robust variant); 1969 (original Granger) | 1969 |
| Ideatore≠ | Hacker & Hatemi-J (robust bootstrap variant); Granger (original causality concept) | Clive W. J. Granger |
| Tipo≠ | Hypothesis test | Time-series predictive causality test |
| Fonte seminale≠ | Hacker, R. S., & Hatemi-J, A. (2006). Tests for causality between integrated variables using asymptotic and bootstrap distributions: Theory and application. Applied Economics, 38(13), 1489–1500. DOI ↗ | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗ |
| Alias | bootstrap Granger causality, heteroscedasticity-robust Granger causality, non-asymptotic Granger causality test, RGC | Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi |
| Correlati≠ | 4 | 5 |
| Sintesi≠ | Robust Granger causality extends the classic Granger causality framework by using bootstrap-based or heteroscedasticity-robust critical values rather than asymptotic chi-squared tables. This makes the test reliable in finite samples and when the data exhibit non-normality, heteroscedasticity, or near-integration, settings where the standard F- or Wald-based test is known to over-reject. | 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. |
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