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| 구조적 단절 확률 효과 모형× | Zivot-Andrews 구조적 변화 검정× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1998–2000s | 1992 |
| 창시자≠ | Bai & Perron (break detection); Baltagi (panel RE framework) | Eric Zivot and Donald W. K. Andrews |
| 유형≠ | Panel regression with regime shifts | Unit root test with endogenous structural break |
| 원전≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. 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 ↗ |
| 별칭 | RE model with structural breaks, break-adjusted random effects, random effects break model, panel RE with regime shifts | ZA test, Zivot-Andrews unit root test, endogenous structural break unit root test, ZA structural break test |
| 관련≠ | 5 | 6 |
| 요약≠ | The structural break random effects model extends standard panel RE estimation by allowing one or more breakpoints at which slope coefficients or error variances shift across time. It combines structural change detection (e.g., Bai-Perron) with the GLS-based random effects estimator, producing regime-specific parameter estimates while retaining the efficiency gains of pooling individual-level variation as random draws from a common distribution. | The Zivot-Andrews (ZA) test is a unit root test that endogenously identifies the most likely location of a single structural break in a time series. Unlike the standard ADF test, it does not require the researcher to pre-specify when the break occurred, making it robust to data-driven regime shifts such as policy changes, financial crises, or major economic events. |
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