Methoden vergelijken

	Panel Data Synthetic Control Method	Matching Estimator
Vakgebied	Causale inferentie	Causale inferentie
Familie	Regression model	Regression model
Jaar van ontstaan	2010	1973
Grondlegger	Alberto Abadie, Alexis Diamond & Jens Hainmueller	Rubin (1973); large-sample theory by Abadie & Imbens (2006)
Type	Causal inference / panel data	Nonparametric matching / causal inference
Oorspronkelijke bron	Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505.	Abadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267.
Aliassen	SCM panel, panel synthetic control, synthetic control estimator, comparative case study	nearest-neighbor matching, NNM, matching on covariates, covariate matching
Verwant	5	6
Samenvatting	The panel data synthetic control method estimates the causal effect of an intervention on a single treated unit by constructing a data-driven weighted combination of untreated units — a synthetic control — that best reproduces the treated unit's pre-treatment outcome trajectory. The post-treatment gap between the treated unit and its synthetic counterpart is the estimated treatment effect.	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.