Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo de efectos fijos no lineal× | Modelo de datos de panel dinámico× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1984 | 1988–1991 |
| Autor original≠ | Gary Chamberlain | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| Tipo≠ | Panel data estimator | Dynamic regression / GMM estimation |
| Fuente seminal≠ | Chamberlain, G. (1984). Panel data. In Z. Griliches & M. D. Intriligator (Eds.), Handbook of Econometrics (Vol. 2, pp. 1247–1318). Elsevier. link ↗ | 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 | nonlinear FE model, NLFE, conditional fixed effects model, incidental parameters model | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model |
| Relacionados | 5 | 5 |
| Resumen≠ | The nonlinear fixed effects model extends fixed effects panel estimation to outcomes governed by nonlinear response functions — such as binary, count, or censored outcomes — while absorbing unobserved individual heterogeneity through unit-specific intercepts. Key special cases include conditional logit for binary outcomes and Poisson fixed effects for count data. | 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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