Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Robustní test jednotkového kořene Phillips-Perron (PP)× | Phillipsův-Perronův test jednotkového kořene× | |
|---|---|---|
| Obor | Ekonometrie | Ekonometrie |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 1988 (base); 2000s–2010s (robust extensions) | 1988 |
| Tvůrce≠ | Phillips & Perron (1988); robustification by Cavaliere & Taylor (2008) and related authors | Peter C. B. Phillips and Pierre Perron |
| Typ≠ | Unit root / stationarity test | Hypothesis test (unit root) |
| Původní zdroj | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| Další názvy | robust Phillips-Perron test, heteroskedasticity-robust PP test, nonparametric robust unit root test, robust PP | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| Příbuzné≠ | 6 | 5 |
| Shrnutí≠ | The Robust Phillips-Perron unit root test extends the classical PP test by applying corrections — such as heteroskedasticity-consistent covariance estimation or wild-bootstrap critical values — that maintain valid inference when the error variance of a time series is non-constant or exhibits unconditional heteroskedasticity, conditions under which the standard PP test is severely size-distorted. | 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. |
| ScholarGateDatová sada ↗ |
|
|