Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Критерій одиничного кореня Ламсдейна-Папелла з двома структурними розривами× | Тест Живота-Ендрюса на одиничний корінь з одним структурним розривом× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Hypothesis test | Hypothesis test |
| Рік появи≠ | 1997 | 1992 |
| Автор методу≠ | Robin Lumsdaine & David Papell | Eric Zivot & Donald Andrews |
| Тип≠ | Sequential two-break unit-root test | Sequential unit-root test with endogenous break-point selection |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви | 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 |
| Пов'язані | 3 | 3 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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