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반사실적 영향 평가 (CIE)×이중차분법 (Diff-in-Diff)×
분야인과추론계량경제학
계열Regression modelRegression model
기원 연도1970s–2000s1994
창시자Heckman, Imbens, Rubin, and the program evaluation literatureCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
유형Causal inference / program evaluationCausal inference / panel regression
원전Heckman, 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
별칭CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluationdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
관련55
요약Counterfactual 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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ScholarGate방법 비교: Counterfactual Impact Evaluation · Difference-in-Differences. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare