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Panel Data Coarsened Exact Matching (Panel Data CEM)×Diferenču starpībām (Diff-in-Diff)×
NozareCēloņsakarību secināšanaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads2012 (CEM); 2021 (panel extension)1994
AutorsIacus, King & Porro (CEM, 2012); panel extension via Imai, Kim & Wang (2021)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipsMatching / quasi-experimentalCausal inference / panel regression
PirmavotsIacus, 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
Citi nosaukumiPanel CEM, CEM for panel data, coarsened exact matching with panel datadiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Saistītās65
KopsavilkumsPanel Data Coarsened Exact Matching applies the Coarsened Exact Matching (CEM) algorithm to repeated-measures panel data, matching treated and control units within the same coarsened covariate strata across multiple time periods. It balances pre-treatment characteristics before estimating a causal treatment effect, combining the transparency of exact matching with the richer identification available in longitudinal datasets.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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ScholarGateSalīdzināt metodes: Panel Data Coarsened Exact Matching · Difference-in-Differences. Izgūts 2026-06-17 no https://scholargate.app/lv/compare