Comparer des méthodes

	GMM pour systèmes non linéaires	Méthode des variables instrumentales (VI) pour l'inférence causale
Domaine	Économétrie	Économie de la santé
Famille	Regression model	Process / pipeline
Année d'origine	1982	1990s (modern applications)
Auteur d'origine	Lars Peter Hansen	Angrist & Pischke (applied econometrics); rooted in econometric theory
Type	System estimator	Method
Source fondatrice	Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica, 50(4), 1029–1054.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Alias	NLS-GMM, nonlinear system generalized method of moments, system GMM for nonlinear models, NL-SGMM	IV, two-stage least squares, TSLS, causal estimation
Apparentées	4	3
Résumé	Nonlinear System GMM extends the Generalized Method of Moments framework to estimate a system of structural equations in which the parameter vector enters the moment conditions nonlinearly. It jointly exploits moment restrictions across multiple equations, yielding efficiency gains over single-equation approaches when the equations share parameters or have correlated disturbances.	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.