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Robust System GMM×Metoda instrumentálních proměnných (IV) pro kauzální inferenci×
OborEkonometrieEkonomika zdravotnictví
RodinaRegression modelProcess / pipeline
Rok vzniku1998–20051990s (modern applications)
TvůrceBlundell & Bond (1998); robustness corrections by Windmeijer (2005)Angrist & Pischke (applied econometrics); rooted in econometric theory
TypPanel data GMM estimatorMethod
Původní zdrojBlundell, 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 ↗
Další názvysystem GMM with robust standard errors, two-step system GMM, Blundell-Bond robust estimator, robust S-GMMIV, two-stage least squares, TSLS, causal estimation
Příbuzné53
ShrnutíRobust 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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ScholarGatePorovnat metody: Robust System GMM · Instrumental Variables in Health Research. Získáno 2026-06-18 z https://scholargate.app/cs/compare