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| 강건 패널 데이터 분석× | 강건 OLS (강건 표준 오차를 사용한 OLS)× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1987 | 1980 |
| 창시자≠ | Arellano (1987); White (1980) heteroscedasticity-consistent framework | Halbert White |
| 유형≠ | Robust estimation / inference correction | Linear regression with robust inference |
| 원전≠ | Arellano, 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 ↗ |
| 별칭 | 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 |
| 관련 | 6 | 6 |
| 요약≠ | 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. |
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