Comparar métodos

	Modelo de datos de panel dinámico	Estimador de Mínimos Cuadrados Generalizados (GMM) de Arellano-Bond
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1991–1998	1991
Autor original	Arellano & Bond (1991); Blundell & Bond (1998)	Manuel Arellano and Stephen Bond
Tipo	Dynamic panel regression	GMM estimator for dynamic panel data
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.	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.
Alias	dynamic panel model, lagged dependent variable panel model, Arellano-Bond type dynamic panel, GMM dynamic panel	AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator
Relacionados	5	5
Resumen	The dynamic panel data model extends standard panel regression by including one or more lagged values of the outcome variable as regressors. Because past outcomes directly predict current outcomes, the model captures persistence and adjustment dynamics — but it also introduces a correlation between the lagged dependent variable and the individual fixed effect, rendering OLS and standard fixed-effects estimators inconsistent. GMM-based approaches developed by Arellano-Bond and Blundell-Bond resolve this problem.	The Arellano-Bond GMM estimator is the standard approach for dynamic panel data models in which the lagged dependent variable appears as a regressor. By first-differencing to remove fixed effects and using deeper lags as instruments, it yields consistent estimates even when the error is serially correlated and regressors are endogenous.