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Variáveis Instrumentais via Mínimos Quadrados em Dois Estágios (IV/2SLS)×Estimativa Duplamente Robusta (AIPW)×
ÁreaInferência causalInferência causal
FamíliaRegression modelRegression model
Ano de origem20092005
Autor originalAngrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)Robins & Rotnitzky; Bang & Robins
TipoInstrumental-variables regressionSemiparametric causal estimator
Fonte 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 ↗
Outros nomesinstrumental variables, IV estimation, 2SLS, instrumental variable regressionAIPW, augmented inverse probability weighting, doubly robust estimator, Çift Gürbüz Kestirici (Augmented IPW / AIPW)
Relacionados55
ResumoIV/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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ScholarGateComparar métodos: Two-Stage Least Squares (2SLS) · Doubly Robust Estimation. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare