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異質的治療効果粗化厳密マッチング×差分の差 (Difference-in-Differences, DiD)×
分野因果推論計量経済学
系統Regression modelRegression model
提唱年2012-20131994
提唱者Iacus, King & Porro (CEM foundation, 2012); subgroup HTE extensions by Imai & colleaguesCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
種類Matching-based causal inference with subgroup CATE estimationCausal inference / panel regression
原典Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
別名HTE-CEM, CEM with CATE estimation, subgroup CEM, coarsened exact matching with effect heterogeneitydiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
関連55
概要Heterogeneous treatment effect coarsened exact matching (HTE-CEM) extends the coarsened exact matching framework to estimate how treatment effects vary across subgroups or individual characteristics. After CEM creates balanced strata by coarsening continuous covariates into bins and exactly matching units within each bin, conditional average treatment effects (CATEs) are computed within or across these strata, revealing where treatment works, for whom, and by how much.Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.
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ScholarGate手法を比較: Heterogeneous Treatment Effect Coarsened Exact Matching · Difference-in-Differences. 2026-06-19に以下より取得 https://scholargate.app/ja/compare