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回帰不連続デザイン(Regression Discontinuity Design, RDD)×操作変数法(IV/2SLS)による推定×
分野因果推論因果推論
系統Regression modelRegression model
提唱年20082009
提唱者Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)
種類Quasi-experimental causal designInstrumental-variables regression
原典Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
別名RDD, regression discontinuity design, sharp RDD, fuzzy RDDinstrumental variables, IV estimation, 2SLS, instrumental variable regression
関連55
概要Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold.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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ScholarGate手法を比較: Regression Discontinuity · Two-Stage Least Squares (2SLS). 2026-06-18に以下より取得 https://scholargate.app/ja/compare