ScholarGate
Асистент

Сравнение на методи

Прегледайте избраните методи един до друг; редовете с разлики са откроени.

Модел със здрави фиксирани ефекти×Robust OLS (OLS с робастни стандартни грешки)×
ОбластИконометрияИконометрия
СемействоRegression modelRegression model
Година на възникване19871980
СъздателManuel ArellanoHalbert White
ТипPanel regression with robust inferenceLinear regression with robust inference
Основополагащ източникArellano, M. (1987). Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434. link ↗White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗
Други названияFE with robust standard errors, cluster-robust fixed effects, fixed effects with heteroscedasticity-robust SE, within estimator with robust inferenceHC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors
Свързани56
РезюмеThe robust fixed effects model combines the within-group estimator for panel data with variance-covariance matrices that remain valid under heteroscedasticity and within-unit error correlation. Introduced by Arellano (1987), cluster-robust standard errors paired with the fixed effects estimator are now the default approach for credible panel data inference in economics and social science.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.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

Към търсенето Изтегляне на слайдове

ScholarGateСравнение на методи: Robust Fixed Effects Model · Robust OLS. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare