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| Ước lượng Hệ thống GMM Mạnh mẽ× | Phương pháp Biến Công cụ (IV) cho Suy luận Nhân quả× | |
|---|---|---|
| Lĩnh vực≠ | Kinh tế lượng | Kinh tế học y tế |
| Họ≠ | Regression model | Process / pipeline |
| Năm ra đời≠ | 1998–2005 | 1990s (modern applications) |
| Người khởi xướng≠ | Blundell & Bond (1998); robustness corrections by Windmeijer (2005) | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| Loại≠ | Panel data GMM estimator | Method |
| Công trình gốc≠ | Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| Tên gọi khác | system GMM with robust standard errors, two-step system GMM, Blundell-Bond robust estimator, robust S-GMM | IV, two-stage least squares, TSLS, causal estimation |
| Liên quan≠ | 5 | 3 |
| Tóm tắt≠ | Robust System GMM is a two-step panel data estimator that combines the difference and levels moment conditions of Blundell and Bond (1998) with Windmeijer's (2005) finite-sample correction to the two-step variance, producing valid inference even in short panels with a persistent dependent variable, individual fixed effects, and potentially endogenous regressors. | 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. |
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