Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test de Cointégration Robuste de Johansen× | Test de cointégration de Johansen sur données de panel× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1988–2010 | 2001 |
| Auteur d'origine≠ | Johansen (1988, 1991); robust extensions by Cavaliere, Rahbek, Taylor (2010) and others | Larsson, Lyhagen & Lothgren (building on Johansen 1988/1991) |
| Type≠ | Cointegration rank test (robust variant) | Panel cointegration test |
| Source fondatrice≠ | Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551–1580. DOI ↗ | Larsson, R., Lyhagen, J., & Lothgren, M. (2001). Likelihood-based cointegration tests in heterogeneous panels. Econometrics Journal, 4(1), 109–142. DOI ↗ |
| Alias | outlier-robust Johansen test, robust trace test, robust maximum eigenvalue test, robust cointegration rank test | panel Johansen test, Larsson-Lyhagen-Lothgren test, LLL panel cointegration, panel trace test |
| Apparentées | 5 | 5 |
| Résumé≠ | The Robust Johansen Cointegration test extends the classical Johansen (1988, 1991) likelihood-ratio framework for determining the cointegrating rank of a multivariate I(1) system to settings where standard Gaussian assumptions fail — in particular when the data exhibit outliers, fat-tailed innovations, or conditional heteroskedasticity. Robust modifications adjust residuals, re-weight observations, or bootstrap critical values so that rank inference remains valid under these violations. | The Panel Johansen cointegration test extends Johansen's maximum-likelihood framework to panel data, allowing researchers to test whether multiple non-stationary variables share long-run equilibrium relationships across cross-sectional units. It pools the likelihood-ratio statistics from individual Johansen tests and compares the standardised average against a standard normal distribution, yielding greater power than single-country approaches. |
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