Comparar métodos

	Análise Robusta de Dados em Painel	OLS Robusto (OLS com Erros Padrão Robustos)
Área	Econometria	Econometria
Família	Regression model	Regression model
Ano de origem	1987	1980
Autor original	Arellano (1987); White (1980) heteroscedasticity-consistent framework	Halbert White
Tipo	Robust estimation / inference correction	Linear regression with robust inference
Fonte seminal	Arellano, M. (1987). Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434.	White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.
Outros nomes	robust panel regression, cluster-robust panel estimation, panel regression with robust standard errors, HC/CR panel estimator	HC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors
Relacionados	6	6
Resumo	Robust 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.	Robust OLS applies ordinary least squares to estimate coefficients and then replaces the classical standard errors with heteroscedasticity-consistent (HC) standard errors — commonly called White standard errors. This leaves the point estimates unchanged while yielding valid t-statistics and confidence intervals even when the error variance is not constant across observations.