方法对比

	Robust System GMM	因果推断的工具变量（IV）方法
领域	计量经济学	卫生经济学
方法族	Regression model	Process / pipeline
起源年份	1998–2005	1990s (modern applications)
提出者	Blundell & Bond (1998); robustness corrections by Windmeijer (2005)	Angrist & Pischke (applied econometrics); rooted in econometric theory
类型	Panel data GMM estimator	Method
开创性文献	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.
别名	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
相关	5	3
摘要	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.