Сравнение методов

	Нелинейный разностный GMM	Метод инструментальных переменных (ИП) для причинно-следственного вывода
Область	Эконометрика	Экономика здравоохранения
Семейство	Regression model	Process / pipeline
Год появления	1991–2010	1990s (modern applications)
Автор метода	Wooldridge; building on Arellano and Bond (1991)	Angrist & Pischke (applied econometrics); rooted in econometric theory
Тип	Nonlinear panel estimator	Method
Основополагающий источник	Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 9780262232586	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Другие названия	nonlinear diff-GMM, nonlinear Arellano-Bond GMM, first-difference nonlinear GMM, NL-GMM	IV, two-stage least squares, TSLS, causal estimation
Связанные	5	3
Сводка	Nonlinear Difference GMM extends the Arellano-Bond difference GMM estimator to models where the structural relationship between the outcome and its predictors is inherently nonlinear. By first-differencing to eliminate individual fixed effects and then applying GMM moment conditions with lagged levels as instruments, it consistently estimates parameters in dynamic panel settings without requiring a linear functional form.	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.