Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Paneļa Zivot-Andrews strukturālās izmaiņas vienības saknes tests× | Paneļa Filipsa-Perona vienības saknes tests× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1992 (panel extension: 2000s) | 1988 (original PP); panel adaptation widely established by 2003 |
| Autors≠ | Zivot & Andrews (1992); extended to panel settings by subsequent literature | Phillips & Perron (1988); panel extension by Im, Pesaran & Shin (2003) |
| Tips≠ | Unit root test with endogenous structural break | Nonparametric unit root test |
| Pirmavots≠ | 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 ↗ | Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53-74. DOI ↗ |
| Citi nosaukumi | panel ZA test, panel structural break unit root test, Zivot-Andrews panel unit root test, panel endogenous break unit root test | Panel PP test, Phillips-Perron panel unit root, Im-Pesaran-Shin PP panel test, panel nonparametric unit root test |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | The Panel Zivot-Andrews test extends the single-series Zivot-Andrews (1992) structural break unit root test to panel data, allowing each cross-sectional unit to have its own endogenously determined break date. It tests the null of a unit root against the alternative of stationarity with a one-time structural break, accounting for regime shifts that bias standard panel unit root tests toward false non-rejection. | The Panel PP unit root test extends the nonparametric Phillips-Perron correction for serial correlation to a multi-individual panel setting. It tests the null hypothesis that all cross-sectional units contain a unit root, using a pooled or averaged PP-type statistic that is robust to heteroscedastic and serially correlated errors without requiring explicit lag selection. |
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