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| Test de racine unitaire ADF non linéaire (Test KSS)× | Le test KPSS non linéaire× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2003 | 2006 |
| Auteur d'origine≠ | Kapetanios, Shin, and Snell | Becker, Enders & Lee |
| Type≠ | Nonlinear unit root test | Stationarity test (null: stationary) |
| Source fondatrice≠ | 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 ↗ | Becker, R., Enders, W., & Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. DOI ↗ |
| Alias | KSS test, nonlinear unit root test, ESTAR unit root test, Kapetanios-Shin-Snell test | KPSS nonlinearity test, nonlinear stationarity test, flexible Fourier KPSS, NL-KPSS |
| Apparentées≠ | 6 | 3 |
| Résumé≠ | 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 nonlinear KPSS test extends the classic Kwiatkowski-Phillips-Schmidt-Shin stationarity test by modelling unknown smooth structural breaks in the deterministic trend using a Fourier approximation. Under the null hypothesis the series is stationary around a flexible nonlinear trend, guarding against spurious unit-root findings caused by regime shifts or gradual transitions. |
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