Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Time-varying parameter PP unit root test× | Filipsa-Perona (PP) vienības saknes tests× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1988-1999 | 1988 |
| Autors≠ | Extension of Phillips & Perron (1988); TVP framework attributed to Hall & Luginbuhl (1999) and related literature | Peter C. B. Phillips & Pierre Perron |
| Tips≠ | Unit root test with time-varying parameters | Unit-root test for stationarity |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi≠ | TVP-PP unit root test, time-varying PP test, Phillips-Perron test with time-varying parameters, TVP unit root test | PP test, Phillips-Perron unit root test, Phillips-Perron birim kök testi |
| Saistītās≠ | 3 | 4 |
| Kopsavilkums≠ | The time-varying parameter PP unit root test extends the classical Phillips-Perron test by allowing the autoregressive coefficient to change over time. It detects stochastic non-stationarity in series whose persistence may shift across regimes or periods, offering more reliable inference when structural change is suspected in the data-generating process. | The Phillips-Perron test, proposed by Peter Phillips and Pierre Perron in 1988, tests for a unit root in a time series, like the Augmented Dickey-Fuller test, but corrects for autocorrelation and heteroskedasticity in the errors non-parametrically rather than by adding lagged differences. It runs a simple Dickey-Fuller regression and then adjusts the test statistic using a long-run variance estimate, so the practitioner need not choose a lag length for the regression itself. |
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