Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Testul de cauzalitate asimetric Hatemi-J× | Testul de cauzalitate Granger× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie≠ | Hypothesis test | Regression model |
| Anul apariției≠ | 2012 | 1969 |
| Autorul original≠ | Abdulnasser Hatemi-J | Clive W. J. Granger |
| Tip≠ | Nonlinear Granger causality test | Time-series predictive causality test |
| Sursa seminală≠ | Hatemi-J, A. (2012). Asymmetric causality tests with an application. Empirical Economics, 43(1), 447–456. DOI ↗ | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗ |
| Denumiri alternative | Hatemi-J Asymmetric Causality Test, Asymmetric Causality Test, Positive and Negative Causality Test, Asimetrik Nedensellik Testi | Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi |
| Înrudite≠ | 3 | 5 |
| Rezumat≠ | The Hatemi-J asymmetric causality test, introduced by Abdulnasser Hatemi-J in 2012, extends the Granger causality framework to allow causal relationships between the positive and negative components of integrated time series to differ. By decomposing each series into cumulative positive and negative partial sums and embedding the Toda-Yamamoto approach within a VAR, the test enables researchers to distinguish whether positive shocks, negative shocks, or both drive causation between economic variables. | 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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