Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Ajuste frontal (Criterio Frontdoor)× | Variables Instrumentales mediante Mínimos Cuadrados en Dos Etapas (IV/2SLS)× | |
|---|---|---|
| Campo | Inferencia causal | Inferencia causal |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1995 | 2009 |
| Autor original≠ | Judea Pearl | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) |
| Tipo≠ | Causal identification (graphical adjustment) | Instrumental-variables regression |
| Fuente seminal≠ | Pearl, J. (1995). Causal Diagrams for Empirical Research. Biometrika, 82(4), 669-688. DOI ↗ | Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Alias≠ | frontdoor criterion, Pearl's frontdoor adjustment, frontdoor formula, Ön Kapı Düzenlemesi (Frontdoor Adjustment) | instrumental variables, IV estimation, 2SLS, instrumental variable regression |
| Relacionados≠ | 4 | 5 |
| Resumen≠ | Frontdoor adjustment is Judea Pearl's graphical identification strategy, introduced in 1995, that recovers the causal effect of a treatment on an outcome through a fully mediating variable even when an unobserved confounder sits between the treatment and the outcome. It is the go-to tool when the backdoor criterion cannot be satisfied because the confounder is unmeasured. | 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). |
| ScholarGateConjunto de datos ↗ |
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