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베이즈 퍼지 회귀 불연속성×이중차분법 (Diff-in-Diff)×
분야인과추론계량경제학
계열Regression modelRegression model
기원 연도2001 (fuzzy RD identification); 2016 (Bayesian formulation by Chib & Jacobi)1994
창시자Chib & Jacobi (Bayesian formulation); Hahn, Todd & Van der Klaauw (fuzzy RD identification)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
유형Bayesian causal inference / quasi-experimental designCausal inference / panel regression
원전Hahn, J., Todd, P., & Van der Klaauw, W. (2001). Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design. Review of Economic Studies, 68(1), 201-209. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
별칭Bayesian Fuzzy RD, Bayesian Fuzzy RDD, Fuzzy RD with Bayesian Inferencediff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
관련55
요약Bayesian Fuzzy Regression Discontinuity (Bayesian Fuzzy RD) combines the quasi-experimental logic of fuzzy regression discontinuity design with full Bayesian inference. It estimates a local average treatment effect at a policy threshold where treatment assignment is probabilistic rather than deterministic, placing prior distributions over all unknowns and recovering a complete posterior distribution of the causal effect rather than a single point estimate.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: Bayesian Fuzzy Regression Discontinuity · Difference-in-Differences. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare