So sánh phương pháp

	Biến Công Cụ (IV) cho Hiệu Ứng Điều Trị Không Đồng Nhất (HTE-IV)	Phương pháp Biến Công cụ (IV) cho Suy luận Nhân quả
Lĩnh vực	Suy luận nhân quả	Kinh tế học y tế
Họ	Regression model	Process / pipeline
Năm ra đời	1994	1990s (modern applications)
Người khởi xướng	Imbens & Angrist	Angrist & Pischke (applied econometrics); rooted in econometric theory
Loại	Causal inference / IV with effect heterogeneity	Method
Công trình gốc	Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Tên gọi khác	HTE-IV, LATE estimator, IV with effect heterogeneity, local average treatment effect IV	IV, two-stage least squares, TSLS, causal estimation
Liên quan	4	3
Tóm tắt	Heterogeneous treatment effect IV applies instrumental variables estimation while explicitly acknowledging and modelling that the treatment effect differs across units. Rather than recovering a single average effect, it focuses on the Local Average Treatment Effect (LATE) — the causal effect for compliers, the subpopulation whose treatment status is actually shifted by the instrument — and extends analysis to variation in that effect across observed subgroups.	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.