Porovnat metody
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| Test jednotkové odmocniny Lee-Strazicich LM se dvěma strukturálními zlomy× | Zivotův-Andrewsův test jednotkových kořenů s jedním zlomem struktury× | |
|---|---|---|
| Obor | Ekonometrie | Ekonometrie |
| Rodina | Hypothesis test | Hypothesis test |
| Rok vzniku≠ | 2003 | 1992 |
| Tvůrce≠ | Junsoo Lee & Mark Strazicich | Eric Zivot & Donald Andrews |
| Typ≠ | Lagrange Multiplier unit-root test with two endogenous structural breaks | Sequential unit-root test with endogenous break-point selection |
| Původní zdroj≠ | Lee, J., & Strazicich, M. C. (2003). Minimum Lagrange multiplier unit root test with two structural breaks. Review of Economics and Statistics, 85(4), 1082–1089. 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 ↗ |
| Další názvy | LS Unit Root Test, Minimum LM Unit Root Test, Lee-Strazicich Two-Break Test, Lee-Strazicich LM Testi | ZA Test, Zivot-Andrews Break Test, Endogenous Break Unit-Root Test, Zivot-Andrews Birim Kök Testi |
| Příbuzné | 3 | 3 |
| Shrnutí≠ | The Lee-Strazicich (2003) test is a Lagrange Multiplier-based unit-root test that allows for two endogenous structural breaks under both the null and alternative hypotheses. Proposed by Junsoo Lee and Mark C. Strazicich, it corrects a fundamental flaw in earlier break-based tests such as Zivot-Andrews, where structural breaks were permitted only under the alternative. By incorporating breaks under the null, the LS test avoids spurious rejections and provides size-correct inference in the presence of level or trend shifts. | 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. |
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