Comparer des méthodes

	Estimateur par appariement sur données de panel	Différence-en-différences sur données de panel (Panel DiD / TWFE)
Domaine	Inférence causale	Inférence causale
Famille	Regression model	Regression model
Année d'origine	1997-2021	1985–2004
Auteur d'origine	Heckman, Ichimura & Todd (1997); Imai, Kim & Wang (2021) for panel extension	Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004)
Type	Quasi-experimental causal estimator	Causal inference / panel regression
Source fondatrice	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.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Alias	panel matching, matching-on-panel-data, longitudinal matching estimator, PDME	Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff
Apparentées	6	4
Résumé	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.	Panel Data Difference-in-Differences extends the classic two-period DiD design to settings with multiple units observed across many time periods. By absorbing unit-level fixed effects and time fixed effects simultaneously, it isolates the causal effect of a treatment or policy change while controlling for both time-invariant unit heterogeneity and common time shocks affecting all units.