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Identifikimi kauzal me Grafet Drejt-ciklike (do-calculus)×Two-Stage Least Squares (2SLS)×
FushaInferenca kauzaleInferenca kauzale
FamiljaRegression modelRegression model
Viti i origjinës20092009
KrijuesiJudea PearlAngrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)
LlojiCausal identification frameworkInstrumental-variables regression
Burimi themeluesPearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. ISBN: 978-0521895606Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Emërtime të tjerado-calculus, backdoor adjustment, Pearl causal identification, DAG ile Nedensel Tanımlama (do-calculus)instrumental variables, IV estimation, 2SLS, instrumental variable regression
Të lidhura55
PërmbledhjaDAG causal identification is a framework, developed by Judea Pearl (2009), that encodes causal assumptions as a directed acyclic graph and uses the do-calculus rules to determine whether and how a causal effect can be identified from observational data. It systematically handles confounders, instrumental variables, and backdoor paths.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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ScholarGateKrahasoni metodat: DAG Causal Identification · Two-Stage Least Squares (2SLS). Marrë më 2026-06-20 nga https://scholargate.app/sq/compare