Сравнение на методи

	Многопериодна контрафактуална оценка на въздействието	Контрафактуална оценка на въздействието (CIE)
Област	Причинно-следствено заключение	Причинно-следствено заключение
Семейство	Regression model	Regression model
Година на възникване	2000s–2010s	1970s–2000s
Създател	Developed through EU policy evaluation practice (European Commission); formalized by Lechner, Caliendo, and related econometricians	Heckman, Imbens, Rubin, and the program evaluation literature
Тип	Causal inference / quasi-experimental evaluation	Causal inference / program evaluation
Основополагащ източник	Caliendo, M., & Kopeinig, S. (2008). Some Practical Guidance for the Implementation of Propensity Score Matching. Journal of Economic Surveys, 22(1), 31-72.	Heckman, J. J., & Vytlacil, E. J. (2007). Econometric evaluation of social programs, Part I: Causal models, structural models and econometric policy evaluation. Handbook of Econometrics, 6B, 4779-4874.
Други названия	multi-period CIE, longitudinal counterfactual evaluation, dynamic counterfactual impact evaluation, multi-wave CIE	CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation
Свързани	4	5
Резюме	Multi-period Counterfactual Impact Evaluation (CIE) estimates the causal effect of a policy or program by constructing what would have happened to treated units across multiple time periods had they not been treated. Unlike single-period evaluations, it tracks treatment effects as they evolve over time, capturing dynamic, delayed, or fading impacts that a two-period comparison would miss.	Counterfactual Impact Evaluation is a family of causal methods that estimates the effect of an intervention by comparing what actually happened to participants with what would have happened had the intervention not taken place. Formalised in the Rubin Causal Model and extended by Heckman, Imbens and others, CIE underlies most modern program and policy evaluation practice.