Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Lumsdaine-Papell vienības saknes tests ar diviem strukturāliem pārtraukumiem× | Života-Endrūsa vienības saknes tests ar vienu strukturālu pārtraukumu× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1997 | 1992 |
| Autors≠ | Robin Lumsdaine & David Papell | Eric Zivot & Donald Andrews |
| Tips≠ | Sequential two-break unit-root test | Sequential unit-root test with endogenous break-point selection |
| Pirmavots≠ | Lumsdaine, R. L., & Papell, D. H. (1997). Multiple trend breaks and the unit-root hypothesis. Review of Economics and Statistics, 79(2), 212–218. DOI ↗ | 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 ↗ |
| Citi nosaukumi | LP Test, Two-Break Unit-Root Test, Double Structural Break Unit-Root Test, Lumsdaine-Papell İki Kırılmalı Birim Kök Testi | ZA Test, Zivot-Andrews Break Test, Endogenous Break Unit-Root Test, Zivot-Andrews Birim Kök Testi |
| Saistītās | 3 | 3 |
| Kopsavilkums≠ | The Lumsdaine-Papell test, introduced by Robin Lumsdaine and David Papell in 1997, extends the Zivot-Andrews single-break unit-root test to allow for two simultaneous structural breaks in the intercept and/or linear trend of a time series. It is widely used in macroeconomics and finance when data are suspected to have experienced two major regime shifts — such as policy changes, financial crises, or wars — and the researcher needs to determine whether the series is nonetheless integrated of order one. | The Zivot-Andrews (ZA) test, introduced by Eric Zivot and Donald Andrews in 1992, is a sequential unit-root test that allows for a single structural break at an unknown date. It extends the augmented Dickey-Fuller framework by endogenously selecting the break point that provides the strongest evidence against the unit-root null hypothesis, making it particularly useful for macroeconomic and financial time series that may have been disrupted by events such as policy changes, financial crises, or supply shocks. |
| ScholarGateDatu kopa ↗ |
|
|