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Estimador de Pareamento para Avaliação de Políticas×Diferenças em Diferenças (DiD)×
ÁreaInferência causalEconometria
FamíliaRegression modelRegression model
Ano de origem1998-20061994
Autor originalHeckman, Ichimura & Todd; Abadie & ImbensCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipoNon-parametric causal estimatorCausal inference / panel regression
Fonte seminalAbadie, A., & Imbens, G. W. (2006). Large sample properties of matching estimators for average treatment effects. Econometrica, 74(1), 235-267. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Outros nomesmatching estimator, program evaluation matching, treatment effect matching, Abadie-Imbens estimatordiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Relacionados65
ResumoThe policy evaluation matching estimator estimates the causal effect of a program or policy on treated units by pairing each participant with one or more non-participants who share similar pre-treatment characteristics. Developed rigorously by Heckman, Ichimura & Todd (1998) and Abadie & Imbens (2006), it avoids parametric outcome models and is the standard non-parametric tool for program and policy evaluation.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.
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ScholarGateComparar métodos: Policy Evaluation Matching Estimator · Difference-in-Differences. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare