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领域计量经济学计量经济学
方法族Regression modelRegression model
起源年份1998–2000s1966
提出者Bai & Perron (break detection); Baltagi (panel RE framework)Balestra & Nerlove
类型Panel regression with regime shiftsPanel data estimator
开创性文献Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗
别名RE model with structural breaks, break-adjusted random effects, random effects break model, panel RE with regime shiftsrandom effects estimator, RE model, GLS random effects, error components model
相关55
摘要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 panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation.
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  3. PUBLISHED

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ScholarGate方法对比: Structural Break Random Effects Model · Panel Random Effects Model. 于 2026-06-15 检索自 https://scholargate.app/zh/compare