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Counterfactual Impact Evaluation (CIE)×Difference-in-Differences (DiD)×
VakgebiedCausale inferentieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan1970s–2000s1994
GrondleggerHeckman, Imbens, Rubin, and the program evaluation literatureCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TypeCausal inference / program evaluationCausal inference / panel regression
Oorspronkelijke bronHeckman, 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. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
AliassenCIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluationdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Verwant55
SamenvattingCounterfactual 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.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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ScholarGateMethoden vergelijken: Counterfactual Impact Evaluation · Difference-in-Differences. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare