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Variables instrumentals mitjançant mínims quadrats en dues etapes (IV/2SLS)×Estimació Doblement Robusta (AIPW)×
CampInferència causalInferència causal
FamíliaRegression modelRegression model
Any d'origen20092005
Autor originalAngrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)Robins & Rotnitzky; Bang & Robins
TipusInstrumental-variables regressionSemiparametric causal estimator
Font seminalAngrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355Robins, J. M. & Rotnitzky, A. (1995). Semiparametric Efficiency in Multivariate Regression Models with Missing Data. Journal of the American Statistical Association, 90(429), 122-129. DOI ↗
Àliesinstrumental variables, IV estimation, 2SLS, instrumental variable regressionAIPW, augmented inverse probability weighting, doubly robust estimator, Çift Gürbüz Kestirici (Augmented IPW / AIPW)
Relacionats55
ResumIV/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).Doubly Robust Estimation, also called Augmented Inverse Probability Weighting (AIPW), is a semiparametric method for estimating causal treatment effects that combines an outcome regression model with a propensity (treatment) model. Developed in the work of Robins & Rotnitzky (1995) and Bang & Robins (2005), it stays consistent as long as at least one of the two models is correctly specified.
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ScholarGateCompara mètodes: Two-Stage Least Squares (2SLS) · Doubly Robust Estimation. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare