Сравнение методов

	Нелинейный тест спецификации Хаусмана	Метод инструментальных переменных (ИП) для причинно-следственного вывода
Область	Эконометрика	Экономика здравоохранения
Семейство	Regression model	Process / pipeline
Год появления	1978 (nonlinear extension developed through 1980s–1990s)	1990s (modern applications)
Автор метода	Jerry A. Hausman	Angrist & Pischke (applied econometrics); rooted in econometric theory
Тип	Specification / endogeneity test	Method
Основополагающий источник	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.
Другие названия	Hausman specification test (nonlinear), nonlinear endogeneity test, Wu-Hausman test (nonlinear), NL-Hausman test	IV, two-stage least squares, TSLS, causal estimation
Связанные	3	3
Сводка	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.