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Modelo de Efectos Aleatorios con Rupturas Estructurales×Prueba de Ruptura Estructural de Zivot-Andrews×
CampoEconometríaEconometría
FamiliaRegression modelRegression model
Año de origen1998–2000s1992
Autor originalBai & Perron (break detection); Baltagi (panel RE framework)Eric Zivot and Donald W. K. Andrews
TipoPanel regression with regime shiftsUnit root test with endogenous structural break
Fuente seminalBai, 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 ↗
AliasRE model with structural breaks, break-adjusted random effects, random effects break model, panel RE with regime shiftsZA test, Zivot-Andrews unit root test, endogenous structural break unit root test, ZA structural break test
Relacionados56
ResumenThe 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.
ScholarGateConjunto de datos
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  2. 2 Fuentes
  3. PUBLISHED
  1. v1
  2. 2 Fuentes
  3. PUBLISHED

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ScholarGateComparar métodos: Structural Break Random Effects Model · Zivot-Andrews Structural Break Test. Recuperado el 2026-06-17 de https://scholargate.app/es/compare