Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель случайных эффектов для панельных данных× | Тест Хаусмана для панельных данных× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1966 | 1978 |
| Автор метода≠ | Balestra & Nerlove | Jerry A. Hausman |
| Тип≠ | Panel data estimator | Specification test |
| Основополагающий источник≠ | Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗ | Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ |
| Другие названия | random effects estimator, RE model, GLS random effects, error components model | Hausman endogeneity test, Wu-Hausman test, fixed-vs-random effects test, Hausman chi-squared test |
| Связанные | 5 | 5 |
| Сводка≠ | The panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation. | 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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