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空間的粗粒化厳密一致法(Spatial CEM)×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 (CEM foundation); spatial extension in applied literature 2015-present1994
提唱者Iacus, King & Porro (CEM foundation, 2012); extended to spatial contexts by applied spatial econometriciansCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
種類Quasi-experimental matching estimator with spatial covariatesCausal 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Spatial CEM, Geographic CEM, Spatial exact matching, CEM with spatial covariatesdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
関連65
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.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: Spatial Coarsened Exact Matching · Difference-in-Differences. 2026-06-17に以下より取得 https://scholargate.app/ja/compare