Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo de datos de panel dinámico× | Modelo de efectos fijos en panel× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1988–1991 | 1978 |
| Autor original≠ | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) |
| Tipo≠ | Dynamic regression / GMM estimation | Panel regression estimator |
| Fuente 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 ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Alias | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model | within estimator, FE model, within-group estimator, LSDV model |
| Relacionados | 5 | 5 |
| Resumen≠ | The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy. | The panel fixed effects (FE) model controls for all time-invariant, unit-specific unobserved heterogeneity by absorbing it into individual intercepts. By sweeping out unit means through the within transformation, FE yields unbiased estimates of the effect of time-varying regressors even when omitted unit-level confounders are correlated with those regressors. |
| ScholarGateConjunto de datos ↗ |
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