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Frontdoor Adjustment (Frontdoor Criterion)×Instrumentālās mainīgās, izmantojot divpakāpju mazāko kvadrātu metodi (IV/2SLS)×
NozareCēloņsakarību secināšanaCēloņsakarību secināšana
SaimeRegression modelRegression model
Izcelsmes gads19952009
AutorsJudea PearlAngrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)
TipsCausal identification (graphical adjustment)Instrumental-variables regression
PirmavotsPearl, 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
Citi nosaukumifrontdoor criterion, Pearl's frontdoor adjustment, frontdoor formula, Ön Kapı Düzenlemesi (Frontdoor Adjustment)instrumental variables, IV estimation, 2SLS, instrumental variable regression
Saistītās45
KopsavilkumsFrontdoor 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).
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ScholarGateSalīdzināt metodes: Frontdoor Adjustment · Two-Stage Least Squares (2SLS). Izgūts 2026-06-18 no https://scholargate.app/lv/compare