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| 강건 시스템 GMM× | 인과 추론을 위한 도구 변수(IV) 방법× | |
|---|---|---|
| 분야≠ | 계량경제학 | 보건경제학 |
| 계열≠ | Regression model | Process / pipeline |
| 기원 연도≠ | 1998–2005 | 1990s (modern applications) |
| 창시자≠ | Blundell & Bond (1998); robustness corrections by Windmeijer (2005) | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| 유형≠ | Panel data GMM estimator | Method |
| 원전≠ | 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 ↗ |
| 별칭 | 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 |
| 관련≠ | 5 | 3 |
| 요약≠ | 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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