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Matchningsestimator×Differens-i-differens (DiD)×
ÄmnesområdeKausal inferensEkonometri
FamiljRegression modelRegression model
Ursprungsår19731994
UpphovspersonRubin (1973); large-sample theory by Abadie & Imbens (2006)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TypNonparametric matching / causal inferenceCausal inference / panel regression
UrsprungskällaAbadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Aliasnearest-neighbor matching, NNM, matching on covariates, covariate matchingdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Närliggande65
SammanfattningThe matching estimator identifies the causal effect of a treatment by pairing each treated unit with one or more untreated units that have similar observed characteristics. Formalised by Rubin (1973) and given rigorous large-sample theory by Abadie and Imbens (2006), it constructs a credible control group from observational data without requiring a parametric model for the outcome.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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ScholarGateJämför metoder: Matching Estimator · Difference-in-Differences. Hämtad 2026-06-15 från https://scholargate.app/sv/compare