Comparer des méthodes

	Variables instrumentales par moindres carrés en deux étapes (VI/2SLS)	Appariement par score de propension
Domaine	Inférence causale	Statistiques de recherche
Famille	Regression model	Process / pipeline
Année d'origine	2009	1983
Auteur d'origine	Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)	Paul Rosenbaum and Donald Rubin
Type	Instrumental-variables regression	Method
Source fondatrice	Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355	Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.
Alias	instrumental variables, IV estimation, 2SLS, instrumental variable regression	PSM, propensity score weighting, covariate balance
Apparentées	5	3
Résumé	IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009).	Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias.