Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Panel Toda-Yamamoto Causalityetest× | Panel Granger Causality Test× | |
|---|---|---|
| Vakgebied | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1995 (panel extension from 2006) | 1988–2012 |
| Grondlegger≠ | Toda & Yamamoto (1995); extended to panel settings by Konya (2006) and others | Holtz-Eakin, Newey & Rosen (1988); Dumitrescu & Hurlin (2012) |
| Type≠ | Causality test (non-causality hypothesis) | Causality test |
| Oorspronkelijke bron≠ | Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗ | Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. DOI ↗ |
| Aliassen | Panel TY causality test, Toda-Yamamoto panel causality, panel modified Wald causality test, panel MWALD causality | panel causality test, Dumitrescu-Hurlin test, heterogeneous panel causality, panel Granger test |
| Verwant | 5 | 5 |
| Samenvatting≠ | The Panel Toda-Yamamoto (PTY) causality test extends the Toda-Yamamoto modified Wald approach to panel data, allowing researchers to test Granger non-causality across multiple cross-sectional units without requiring pre-testing for cointegration or imposing a common causality direction on all units. | 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. |
| ScholarGateGegevensset ↗ |
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