Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Variables Instrumentales mediante Mínimos Cuadrados en Dos Etapas (IV/2SLS)× | Estimación Doblemente Robusta (AIPW)× | |
|---|---|---|
| Campo | Inferencia causal | Inferencia causal |
| Familia | Regression model | Regression model |
| Año de origen≠ | 2009 | 2005 |
| Autor original≠ | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) | Robins & Rotnitzky; Bang & Robins |
| Tipo≠ | Instrumental-variables regression | Semiparametric causal estimator |
| Fuente seminal≠ | Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 | Robins, 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 ↗ |
| Alias≠ | instrumental variables, IV estimation, 2SLS, instrumental variable regression | AIPW, augmented inverse probability weighting, doubly robust estimator, Çift Gürbüz Kestirici (Augmented IPW / AIPW) |
| Relacionados | 5 | 5 |
| Resumen≠ | 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). | 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. |
| ScholarGateConjunto de datos ↗ |
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