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| Nichtlinearer ADF-Einheitswurzeltest (KSS-Test)× | Phillips-Perron-Einheitswurzeltest× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 2003 | 1988 |
| Urheber≠ | Kapetanios, Shin, and Snell | Peter C. B. Phillips and Pierre Perron |
| Typ≠ | Nonlinear unit root test | Hypothesis test (unit root) |
| Wegweisende Quelle≠ | Kapetanios, G., Shin, Y., & Snell, A. (2003). Testing for a unit root in the nonlinear STAR framework. Journal of Econometrics, 112(2), 359-379. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| Aliasnamen | KSS test, nonlinear unit root test, ESTAR unit root test, Kapetanios-Shin-Snell test | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | The Nonlinear ADF unit root test, most prominently operationalized by Kapetanios, Shin, and Snell (2003), extends the classical Augmented Dickey-Fuller test to detect mean reversion that occurs via an Exponential Smooth Transition Autoregressive (ESTAR) process. It tests the null of a unit root against a nonlinear stationary alternative, capturing adjustment dynamics that the standard linear ADF test misses. | The Phillips-Perron (PP) test is a nonparametric unit root test for time series that corrects for serial correlation and heteroscedasticity in the error term without adding lagged differences. Introduced by Phillips and Perron (1988), it applies a kernel-based long-run variance estimator to adjust the Dickey-Fuller statistic, making it robust to a wide class of weakly dependent error processes. |
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