Comparer des méthodes

	Différence-en-différences sur données de panel (Panel DiD / TWFE)	Appariement par score de propension
Domaine	Inférence causale	Statistiques de recherche
Famille	Regression model	Process / pipeline
Année d'origine	1985–2004	1983
Auteur d'origine	Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004)	Paul Rosenbaum and Donald Rubin
Type	Causal inference / panel regression	Method
Source fondatrice	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355	Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.
Alias	Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff	PSM, propensity score weighting, covariate balance
Apparentées	4	3
Résumé	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.	Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias.