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Model náhodných efektov so štrukturálnymi zlomami×Model náhodných efektov pre panelové dáta×
OdborEkonometriaEkonometria
RodinaRegression modelRegression model
Rok vzniku1998–2000s1966
TvorcaBai & Perron (break detection); Baltagi (panel RE framework)Balestra & Nerlove
TypPanel regression with regime shiftsPanel data estimator
Pôvodný zdrojBai, 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 ↗
Ďalšie názvyRE 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
Príbuzné55
ZhrnutieThe 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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ScholarGatePorovnať metódy: Structural Break Random Effects Model · Panel Random Effects Model. Získané 2026-06-15 z https://scholargate.app/sk/compare