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Modello Strutturale Marginale per la Valutazione delle Politiche×Valutazione Controfattuale dell'Impatto (CIE)×
CampoInferenza causaleInferenza causale
FamigliaRegression modelRegression model
Anno di origine20001970s–2000s
IdeatoreJames M. Robins, Miguel A. Hernan, Babette BrumbackHeckman, Imbens, Rubin, and the program evaluation literature
TipoCausal inference / weighted regressionCausal inference / program evaluation
Fonte seminaleRobins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550–560. DOI ↗Heckman, J. J., & Vytlacil, E. J. (2007). Econometric evaluation of social programs, Part I: Causal models, structural models and econometric policy evaluation. Handbook of Econometrics, 6B, 4779-4874. DOI ↗
AliasMSM for policy evaluation, policy MSM, causal MSM, structural policy weighting modelCIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation
Correlati65
SintesiA Policy Evaluation Marginal Structural Model (MSM) is a causal inference framework that estimates the population-average effect of a policy by using inverse probability weighting to create a pseudo-population in which treatment assignment is independent of measured confounders, enabling unbiased comparison of potential outcomes under different policy scenarios from observational data.Counterfactual Impact Evaluation is a family of causal methods that estimates the effect of an intervention by comparing what actually happened to participants with what would have happened had the intervention not taken place. Formalised in the Rubin Causal Model and extended by Heckman, Imbens and others, CIE underlies most modern program and policy evaluation practice.
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ScholarGateConfronta i metodi: Policy Evaluation Marginal Structural Model · Counterfactual Impact Evaluation. Consultato il 2026-06-18 da https://scholargate.app/it/compare