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Analyse de sensibilité spatiale pour la causalité×Méthode des variables instrumentales (VI) pour l'inférence causale×
DomaineInférence causaleÉconomie de la santé
FamilleRegression modelProcess / pipeline
Année d'origine1988–2021 (developed progressively)1990s (modern applications)
Auteur d'origineAnselin (1988) for spatial diagnostics; Reich et al. (2021) for spatial causal frameworksAngrist & Pischke (applied econometrics); rooted in econometric theory
TypeSensitivity / robustness analysisMethod
Source fondatriceAnselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers, Dordrecht. ISBN: 978-9024737322Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗
Aliasspatial causal sensitivity, spatial robustness checks, SSAC, spatial confounding sensitivityIV, two-stage least squares, TSLS, causal estimation
Apparentées63
RésuméSpatial sensitivity analysis for causality systematically tests whether a causal estimate derived from georeferenced data holds up as spatial structure, spillovers, and the choice of spatial weights matrix are varied. Because nearby units often share unmeasured confounders — soil quality, local infrastructure, neighbourhood norms — a naive regression may yield biased causal estimates. This method reveals how fragile or robust a claimed causal effect is to alternative spatial specifications.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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ScholarGateComparer des méthodes: Spatial Sensitivity Analysis for Causality · Instrumental Variables in Health Research. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare