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Paneldata-metoden med propensity score matching×Matchningsestimator×
ÄmnesområdeKausal inferensKausal inferens
FamiljRegression modelRegression model
Ursprungsår1997-19981973
UpphovspersonHeckman, Ichimura & ToddRubin (1973); large-sample theory by Abadie & Imbens (2006)
TypMatching / causal inferenceNonparametric matching / causal inference
UrsprungskällaHeckman, J. J., Ichimura, H., & Todd, P. (1998). Matching as an Econometric Evaluation Estimator. Review of Economic Studies, 65(2), 261-294. DOI ↗Abadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267. DOI ↗
AliasPSM with panel data, longitudinal PSM, panel PSM, difference-in-differences PSMnearest-neighbor matching, NNM, matching on covariates, covariate matching
Närliggande66
SammanfattningPanel data propensity score matching combines the bias-reduction of PSM with the longitudinal structure of panel data, enabling causal estimation of treatment effects by matching treated and control units on observable pre-treatment characteristics and then differencing within matched pairs over time. Developed in the framework of Heckman, Ichimura, and Todd (1998), it is especially valuable when randomisation is infeasible and both selection on observables and time-varying confounding must be addressed simultaneously.The 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.
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ScholarGateJämför metoder: Panel Data Propensity Score Matching · Matching Estimator. Hämtad 2026-06-18 från https://scholargate.app/sv/compare