Comparar métodos

	Modelo de Datos de Panel Dinámico No Lineal	System GMM (Arellano-Bover / Blundell-Bond)
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1981-2005	1998
Autor original	Wooldridge (2005); Honore & Tamer (2006); building on Heckman (1981)	Arellano & Bover (1995); Blundell & Bond (1998)
Tipo	Dynamic panel estimator with nonlinear response	Dynamic panel data estimator
Fuente seminal	Wooldridge, J. M. (2005). Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity. Journal of Applied Econometrics, 20(1), 39-54.	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	nonlinear dynamic panel, dynamic nonlinear panel estimator, NDPDM, nonlinear panel with lagged dependent variable	Arellano-Bover estimator, Blundell-Bond estimator, dynamic panel GMM, Sistem GMM (Arellano-Bover / Blundell-Bond)
Relacionados	3	4
Resumen	The nonlinear dynamic panel data model extends standard panel methods to settings where the outcome is binary, count-valued, or censored and where past realizations of the outcome directly affect current ones. It handles unobserved individual heterogeneity alongside state dependence, disentangling genuine persistence from spurious persistence driven by unmeasured unit characteristics.	System GMM is a generalized method of moments estimator for dynamic panel models that contain a lagged dependent variable. Introduced by Blundell and Bond (1998), building on Arellano and Bover, it augments the differenced equation of the earlier difference GMM (Arellano-Bond) with the equation in levels to deliver consistent estimates when N is large and T is small.