Сравнение методов

	Dynamic Instrumental Variables	Метод инструментальных переменных (ИП) для причинно-следственного вывода
Область	Причинно-следственный вывод	Экономика здравоохранения
Семейство	Regression model	Process / pipeline
Год появления	1991	1990s (modern applications)
Автор метода	Arellano & Bond (1991); extended by Blundell & Bond (1998)	Angrist & Pischke (applied econometrics); rooted in econometric theory
Тип	Dynamic panel causal estimation	Method
Основополагающий источник	Arellano, M., & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, 58(2), 277-297.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Другие названия	Dynamic IV, Dynamic Panel IV, Arellano-Bond GMM, System GMM	IV, two-stage least squares, TSLS, causal estimation
Связанные	5	3
Сводка	Dynamic Instrumental Variables estimation addresses endogeneity in panel models where the outcome depends on its own past values. By first-differencing to remove unit fixed effects and then using lagged levels as instruments for the differenced lagged outcome, it produces consistent causal estimates even when standard OLS or fixed-effects are biased by dynamic feedback.	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.