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Робастен анализ на панелни данни×Модел с произволни ефекти за панелни данни×
ОбластИконометрияИконометрия
СемействоRegression modelRegression model
Година на възникване19871966
СъздателArellano (1987); White (1980) heteroscedasticity-consistent frameworkBalestra & Nerlove
ТипRobust estimation / inference correctionPanel data estimator
Основополагащ източникArellano, M. (1987). Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434. link ↗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 ↗
Други названияrobust panel regression, cluster-robust panel estimation, panel regression with robust standard errors, HC/CR panel estimatorrandom effects estimator, RE model, GLS random effects, error components model
Свързани65
РезюмеRobust panel data analysis applies standard panel estimators — fixed effects, random effects, or pooled OLS — while replacing conventional standard errors with cluster-robust or heteroscedasticity-consistent (HC) variants. The point estimates remain unchanged; what changes is the variance-covariance matrix used for inference, making t-tests and F-tests valid even when errors are heteroscedastic or correlated within cross-sectional units over time.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.
ScholarGateНабор от данни
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  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Robust Panel Data Analysis · Panel Random Effects Model. Извлечено на 2026-06-15 от https://scholargate.app/bg/compare