Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Estimador GMM de Painel Arellano-Bond× | Modelo de Efeitos Aleatórios em Painel× | |
|---|---|---|
| Área | Econometria | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1991 | 1966 |
| Autor original≠ | Manuel Arellano and Stephen Bond | Balestra & Nerlove |
| Tipo≠ | Dynamic panel GMM estimator | Panel data estimator |
| Fonte seminal≠ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297. DOI ↗ | 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 ↗ |
| Outros nomes | Arellano-Bond GMM, AB-GMM, difference GMM estimator, dynamic panel GMM | random effects estimator, RE model, GLS random effects, error components model |
| Relacionados | 5 | 5 |
| Resumo≠ | The Arellano-Bond GMM estimator addresses the two core problems of dynamic panel models — individual fixed effects correlated with the regressors, and the endogeneity introduced by a lagged dependent variable — by first-differencing to remove fixed effects and then using lagged levels of the dependent variable as internal instruments. | 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. |
| ScholarGateConjunto de dados ↗ |
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