Comparer des méthodes

	Test de spécification non linéaire de Hausman	Méthode des variables instrumentales (VI) pour l'inférence causale
Domaine	Économétrie	Économie de la santé
Famille	Regression model	Process / pipeline
Année d'origine	1978 (nonlinear extension developed through 1980s–1990s)	1990s (modern applications)
Auteur d'origine	Jerry A. Hausman	Angrist & Pischke (applied econometrics); rooted in econometric theory
Type	Specification / endogeneity test	Method
Source fondatrice	Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Alias	Hausman specification test (nonlinear), nonlinear endogeneity test, Wu-Hausman test (nonlinear), NL-Hausman test	IV, two-stage least squares, TSLS, causal estimation
Apparentées	3	3
Résumé	The Nonlinear Hausman test extends Hausman's (1978) endogeneity specification test to nonlinear models such as probit, logit, Tobit, and count-data regressions. It tests whether suspected regressors are endogenous — i.e., correlated with the error term — in a model where the outcome or the relationship is inherently nonlinear, ensuring that IV-corrected estimates are necessary.	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.