Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo de efectos fijos× | Modelo de datos de panel dinámico× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1971–1978 | 1988–1991 |
| Autor original≠ | Mundlak (1978); Nerlove (1971); classical panel econometrics | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| Tipo≠ | Panel regression estimator | Dynamic regression / GMM estimation |
| Fuente seminal≠ | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030538002 | 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 ↗ |
| Alias | FE model, within estimator, least squares dummy variable, LSDV regression | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model |
| Relacionados | 5 | 5 |
| Resumen≠ | The fixed effects (FE) model is the workhorse estimator for panel data when unobserved unit-specific characteristics are suspected to correlate with the regressors. By absorbing each entity's time-invariant heterogeneity into a separate intercept, FE isolates the causal effect of within-unit variation and eliminates omitted-variable bias from time-constant confounders. | 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. |
| ScholarGateConjunto de datos ↗ |
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