Salīdzināt metodes

	Robusta paneldatu analīze	Robustā OLS (OLS ar robustām standarta kļūdām)
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1987	1980
Autors	Arellano (1987); White (1980) heteroscedasticity-consistent framework	Halbert White
Tips	Robust estimation / inference correction	Linear regression with robust inference
Pirmavots	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.
Citi nosaukumi	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
Saistītās	6	6
Kopsavilkums	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.