Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Testul Zivot-Andrews cu parametri dependenți de timp pentru rădăcină unitară× | Testul Phillips-Perron pentru Rădăcina Unitară× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1992 (base test); TVP adaptation in later applied work | 1988 |
| Autorul original≠ | Zivot & Andrews (1992); TVP extension in subsequent applied econometrics literature | Peter C. B. Phillips and Pierre Perron |
| Tip≠ | Unit root test with endogenous structural break under time-varying parameters | Hypothesis test (unit root) |
| Sursa seminală≠ | Zivot, E., & Andrews, D. W. K. (1992). Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis. Journal of Business & Economic Statistics, 10(3), 251–270. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| Denumiri alternative≠ | TVP Zivot-Andrews test, time-varying Zivot-Andrews unit root test, TVP-ZA test | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| Înrudite≠ | 6 | 5 |
| Rezumat≠ | The time-varying parameter Zivot-Andrews test extends the classic Zivot-Andrews (1992) structural break unit root test by allowing the regression coefficients to evolve over time. Rather than assuming fixed parameters across the full sample, this approach lets the autoregressive dynamics and break timing adapt through a state-space or rolling framework, improving robustness when economic relationships shift gradually. | 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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