Compară metode

	Testul placebo în cercetarea educațională	Metoda Controlului Sintetic (MCS)
Domeniu	Inferență cauzală	Inferență cauzală
Familie	Regression model	Regression model
Anul apariției	1990s–2000s	2003–2010
Autorul original	Widely adopted in applied econometrics and education research; codified by Imbens, Wooldridge, Lee, and Lemieux	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Tip	Falsification / robustness check	Quasi-experimental causal inference
Sursa seminală	Imbens, G. W., & Wooldridge, J. M. (2009). Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature, 47(1), 5-86.	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.
Denumiri alternative	placebo regression, falsification test, placebo check, fake-treatment test	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Înrudite	4	4
Rezumat	A placebo test is a falsification check used in quasi-experimental education research to validate a causal design. By applying the same estimator to a time period, group, or outcome where no real effect should exist, researchers verify that their identification strategy is not picking up spurious patterns. A statistically significant placebo estimate signals a flaw in the design, while a null result supports its credibility.	The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect.