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이질적 처리 효과 조밀화된 정확 매칭 (Heterogeneous Treatment Effect Coarsened Exact Matching)×이중차분법 (Diff-in-Diff)×
분야인과추론계량경제학
계열Regression modelRegression model
기원 연도2012-20131994
창시자Iacus, King & Porro (CEM foundation, 2012); subgroup HTE extensions by Imai & colleaguesCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
유형Matching-based causal inference with subgroup CATE estimationCausal inference / panel regression
원전Iacus, 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
별칭HTE-CEM, CEM with CATE estimation, subgroup CEM, coarsened exact matching with effect heterogeneitydiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
관련55
요약Heterogeneous 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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ScholarGate방법 비교: Heterogeneous Treatment Effect Coarsened Exact Matching · Difference-in-Differences. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare