Comparar métodos

	Robust System GMM	Método de Variables Instrumentales (VI) para Inferencia Causal
Campo	Econometría	Economía de la salud
Familia	Regression model	Process / pipeline
Año de origen	1998–2005	1990s (modern applications)
Autor original	Blundell & Bond (1998); robustness corrections by Windmeijer (2005)	Angrist & Pischke (applied econometrics); rooted in econometric theory
Tipo	Panel data GMM estimator	Method
Fuente seminal	Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Alias	system GMM with robust standard errors, two-step system GMM, Blundell-Bond robust estimator, robust S-GMM	IV, two-stage least squares, TSLS, causal estimation
Relacionados	5	3
Resumen	Robust System GMM is a two-step panel data estimator that combines the difference and levels moment conditions of Blundell and Bond (1998) with Windmeijer's (2005) finite-sample correction to the two-step variance, producing valid inference even in short panels with a persistent dependent variable, individual fixed effects, and potentially endogenous regressors.	Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes.