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空間的粗粒化厳密一致法(Spatial CEM)×粗化完全マッチング(CEM)×
分野因果推論因果推論
系統Regression modelRegression model
提唱年2012 (CEM foundation); spatial extension in applied literature 2015-present2011-2012
提唱者Iacus, King & Porro (CEM foundation, 2012); extended to spatial contexts by applied spatial econometriciansIacus, King, & Porro
種類Quasi-experimental matching estimator with spatial covariatesMatching / causal inference
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 ↗Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗
別名Spatial CEM, Geographic CEM, Spatial exact matching, CEM with spatial covariatesCEM, coarsened matching, monotonic imbalance bounding matching
関連66
概要Spatial Coarsened Exact Matching applies the Coarsened Exact Matching framework to study designs involving geographic units — neighbourhoods, census tracts, municipalities, or grid cells. Covariates are coarsened into discrete bins and units are matched exactly on those bins, with spatial attributes (location, adjacency, geographic characteristics) incorporated as matching dimensions to control for spatial confounding.Coarsened Exact Matching is a preprocessing method that achieves covariate balance by temporarily coarsening continuous variables into bins, exactly matching treated and control units within those bins, and then discarding all unmatched units. Introduced by Iacus, King, and Porro (2011, 2012), it bounds imbalance on each covariate independently, yielding a matched sample on which any estimator can be applied without relying on a propensity score model.
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  3. PUBLISHED

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ScholarGate手法を比較: Spatial Coarsened Exact Matching · Coarsened Exact Matching. 2026-06-19に以下より取得 https://scholargate.app/ja/compare