Comparar métodos

	Avaliação de Impacto Contrafactual Multiperíodo	Diferenças em Diferenças (DiD)
Área	Inferência causal	Econometria
Família	Regression model	Regression model
Ano de origem	2000s–2010s	1994
Autor original	Developed through EU policy evaluation practice (European Commission); formalized by Lechner, Caliendo, and related econometricians	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Tipo	Causal inference / quasi-experimental evaluation	Causal inference / panel regression
Fonte seminal	Caliendo, M., & Kopeinig, S. (2008). Some Practical Guidance for the Implementation of Propensity Score Matching. Journal of Economic Surveys, 22(1), 31-72.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Outros nomes	multi-period CIE, longitudinal counterfactual evaluation, dynamic counterfactual impact evaluation, multi-wave CIE	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Relacionados	4	5
Resumo	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.	Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.