Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test de Causalité de Granger sur Données de Panel× | Test des bornes ARDL sur données de panel× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1988–2012 | 2001 |
| Auteur d'origine≠ | Holtz-Eakin, Newey & Rosen (1988); Dumitrescu & Hurlin (2012) | Pesaran, Shin & Smith |
| Type≠ | Causality test | Bounds test for cointegration |
| Source fondatrice≠ | Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. DOI ↗ | Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. DOI ↗ |
| Alias | panel causality test, Dumitrescu-Hurlin test, heterogeneous panel causality, panel Granger test | Panel ARDL, Panel bounds testing, Panel ARDL cointegration, Panel PSS bounds test |
| Apparentées≠ | 5 | 6 |
| Résumé≠ | 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 Panel ARDL Bounds Test extends the Pesaran, Shin and Smith (2001) bounds testing procedure to panel data, allowing researchers to test for long-run cointegrating relationships between variables without requiring all series to be integrated of the same order. It is widely used in macro-panel studies where variables may be I(0), I(1), or a mixture of both. |
| ScholarGateJeu de données ↗ |
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