Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Panel Toda-Yamamoto Causalityetest× | Panel VECM (Vector Error Correction Model)× | |
|---|---|---|
| Vakgebied | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1995 (panel extension from 2006) | 1987–1995 |
| Grondlegger≠ | Toda & Yamamoto (1995); extended to panel settings by Konya (2006) and others | Engle & Granger (1987) for VECM; Holtz-Eakin, Newey & Rosen (1988) for panel VAR extension |
| Type≠ | Causality test (non-causality hypothesis) | Multivariate dynamic panel model |
| 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 ↗ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ |
| Aliassen | Panel TY causality test, Toda-Yamamoto panel causality, panel modified Wald causality test, panel MWALD causality | Panel VECM, panel vector error correction model, PVECM, panel cointegrating VAR |
| 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. | Panel VECM combines vector error correction modelling with panel data, simultaneously capturing the long-run cointegrating equilibrium among multiple I(1) variables and their short-run adjustment dynamics across multiple cross-sectional units. It is the standard framework when panel variables share at least one common stochastic trend. |
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