方法证据记录
Policy Evaluation Coarsened Exact Matching
Coarsened Exact Matching (CEM) is a quasi-experimental causal-inference technique that creates balanced treatment and control groups from observational data by temporarily coarsening covariates into bins, exactly matching units within those bins, and then pruning unmatched observations before estimating policy effects. Introduced by Iacus, King, and Porro, CEM belongs to the monotonic imbalance bounding family of matching methods and is especially popular in policy evaluation.
源记录
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Coarsened Exact Matching for Policy Evaluation
分类方法记录 · regression-model / causal-inference
- Iacus, S. M., King, G., & Porro, G. (2012). Causal inference without balance checking: Coarsened exact matching. Political Analysis, 20(1), 1-24. · DOI 10.1093/pan/mpr013
- Iacus, S. M., King, G., & Porro, G. (2011). Multivariate matching methods that are monotonic imbalance bounding. Journal of the American Statistical Association, 106(493), 345-361. · DOI 10.1198/jasa.2011.tm09599
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