Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Ajuste Frontdoor (Critério Frontdoor)× | Variáveis Instrumentais via Mínimos Quadrados em Dois Estágios (IV/2SLS)× | |
|---|---|---|
| Área | Inferência causal | Inferência causal |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1995 | 2009 |
| Autor original≠ | Judea Pearl | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) |
| Tipo≠ | Causal identification (graphical adjustment) | Instrumental-variables regression |
| Fonte 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 |
| Outros nomes≠ | frontdoor criterion, Pearl's frontdoor adjustment, frontdoor formula, Ön Kapı Düzenlemesi (Frontdoor Adjustment) | instrumental variables, IV estimation, 2SLS, instrumental variable regression |
| Relacionados≠ | 4 | 5 |
| Resumo≠ | 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 dados ↗ |
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