Comparer des méthodes

	Estimateur par appariement multi-périodes	Estimateur par appariement sur données de panel
Domaine	Inférence causale	Inférence causale
Famille	Regression model	Regression model
Année d'origine	2005	1997-2021
Auteur d'origine	Abadie (2005); Imbens & Wooldridge (2009)	Heckman, Ichimura & Todd (1997); Imai, Kim & Wang (2021) for panel extension
Type	Quasi-experimental / causal inference	Quasi-experimental causal estimator
Source fondatrice	Abadie, A. (2005). Semiparametric Difference-in-Differences Estimators. Review of Economic Studies, 72(1), 1-19.	Heckman, J. J., Ichimura, H., & Todd, P. E. (1997). Matching as an econometric evaluation estimator: Evidence from evaluating a job training programme. Review of Economic Studies, 64(4), 605-654.
Alias	panel matching estimator, longitudinal matching, multi-wave matching, repeated-cross-section matching	panel matching, matching-on-panel-data, longitudinal matching estimator, PDME
Apparentées	6	6
Résumé	The multi-period matching estimator extends the standard matching framework to settings with multiple time periods, pairing each treated unit to similar untreated units based on pre-treatment covariates or propensity scores, then using within-pair before-after differences to estimate the average treatment effect on the treated (ATT). Leveraging repeated observations, it simultaneously controls for observed confounders and time-invariant unobserved heterogeneity.	The panel data matching estimator identifies causal treatment effects by pairing each treated unit with one or more control units that share similar covariate histories in the pre-treatment periods. By exploiting the longitudinal structure of panel data, it controls for both observed time-varying confounders and stable unit characteristics, estimating the average treatment effect on the treated (ATT) without requiring a parallel-trends assumption.