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कोर्स्ड एग्जैक्ट मैचिंग (CEM)×अंतर-में-अंतर (डिफ-इन-डिफ)×
क्षेत्रकारणात्मक अनुमानअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष2011-20121994
प्रवर्तकIacus, King, & PorroCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
प्रकारMatching / causal inferenceCausal inference / panel regression
मौलिक स्रोतIacus, 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
उपनामCEM, coarsened matching, monotonic imbalance bounding matchingdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
संबंधित65
सारांशCoarsened 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.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.
ScholarGateडेटासेट
  1. v1
  2. 2 स्रोत
  3. PUBLISHED
  1. v1
  2. 2 स्रोत
  3. PUBLISHED

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ScholarGateविधियों की तुलना करें: Coarsened Exact Matching · Difference-in-Differences. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare