Porovnat metody

	Párování na základě skóre propensity v panelových datech	Odhad založený na párování
Obor	Kauzální inference	Kauzální inference
Rodina	Regression model	Regression model
Rok vzniku	1997-1998	1973
Tvůrce	Heckman, Ichimura & Todd	Rubin (1973); large-sample theory by Abadie & Imbens (2006)
Typ	Matching / causal inference	Nonparametric matching / causal inference
Původní zdroj	Heckman, J. J., Ichimura, H., & Todd, P. (1998). Matching as an Econometric Evaluation Estimator. Review of Economic Studies, 65(2), 261-294.	Abadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267.
Další názvy	PSM with panel data, longitudinal PSM, panel PSM, difference-in-differences PSM	nearest-neighbor matching, NNM, matching on covariates, covariate matching
Příbuzné	6	6
Shrnutí	Panel 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.