Comparar métodos

	Impact Evaluation Design	Avaliação de Impacto Contrafactual (AIC)
Área	Public Policy	Inferência causal
Família	Process / pipeline	Regression model
Ano de origem	2016	1970s–2000s
Autor original	Development and program-evaluation community; codified by Gertler et al. (World Bank)	Heckman, Imbens, Rubin, and the program evaluation literature
Tipo	Design framework for causal impact evaluation	Causal inference / program evaluation
Fonte seminal	Gertler, P. J., Martinez, S., Premand, P., Rawlings, L. B., & Vermeersch, C. M. J. (2016). Impact Evaluation in Practice (2nd ed.). Washington, DC: World Bank. ISBN: 9781464807794	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.
Outros nomes	Impact Evaluation, Causal Impact Evaluation Design, Counterfactual Evaluation Design	CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation
Relacionados	3	5
Resumo	Impact evaluation design is the upstream task of structuring an evaluation so that it can credibly attribute changes in outcomes to a policy or program rather than to other factors. Its defining concern is the counterfactual: what would have happened to participants in the absence of the intervention. Codified in resources such as the World Bank's Impact Evaluation in Practice, the design process selects an identification strategy — randomised assignment, or a quasi-experimental method such as difference-in-differences, regression discontinuity, instrumental variables or matching — that constructs a valid comparison and yields an unbiased estimate of the intervention's effect.	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.