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Compară metode

Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Potrivirea Exactă Coarsened (CEM)×Difference-in-Differences (Diff-in-Diff)×
DomeniuInferență cauzalăEconometrie
FamilieRegression modelRegression model
Anul apariției2011-20121994
Autorul originalIacus, King, & PorroCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipMatching / causal inferenceCausal inference / panel regression
Sursa seminalăIacus, 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
Denumiri alternativeCEM, coarsened matching, monotonic imbalance bounding matchingdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Înrudite65
RezumatCoarsened 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.
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ScholarGateCompară metode: Coarsened Exact Matching · Difference-in-Differences. Preluat la 2026-06-17 de pe https://scholargate.app/ro/compare