Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Робастный анализ панельных данных× | Тест Хаусмана для панельных данных× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1987 | 1978 |
| Автор метода≠ | Arellano (1987); White (1980) heteroscedasticity-consistent framework | Jerry A. Hausman |
| Тип≠ | Robust estimation / inference correction | Specification test |
| Основополагающий источник≠ | Arellano, M. (1987). Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434. link ↗ | Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ |
| Другие названия | robust panel regression, cluster-robust panel estimation, panel regression with robust standard errors, HC/CR panel estimator | Hausman endogeneity test, Wu-Hausman test, fixed-vs-random effects test, Hausman chi-squared test |
| Связанные≠ | 6 | 5 |
| Сводка≠ | 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. | The Hausman specification test for panel data determines whether individual-specific effects are correlated with the regressors — a correlation that would make the random effects estimator inconsistent. A statistically significant result favours the fixed effects model; a non-significant result supports the more efficient random effects model. |
| ScholarGateНабор данных ↗ |
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