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Неясна регресионна прекъснатост за оценка на политики×Метод на разликите в разликите (Difference-in-Differences, DiD)×
ОбластПричинно-следствено заключениеИконометрия
СемействоRegression modelRegression model
Година на възникване20011994
СъздателHahn, Todd & Van der KlaauwCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
ТипQuasi-experimental / local IV estimatorCausal inference / panel regression
Основополагащ източникHahn, 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
Други названияFuzzy RDD, Fuzzy RD, Fuzzy Regression Discontinuity, Imperfect Compliance RDDdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Свързани55
РезюмеFuzzy Regression Discontinuity Design (Fuzzy RDD) estimates the causal effect of a policy when eligibility is determined by crossing a threshold on a continuous score, but actual take-up or compliance is imperfect. Developed formally by Hahn, Todd, and Van der Klaauw (2001), it uses the threshold as an instrumental variable to recover a Local Average Treatment Effect (LATE) among compliers near the cutoff.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.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Policy Evaluation Fuzzy Regression Discontinuity · Difference-in-Differences. Извлечено на 2026-06-18 от https://scholargate.app/bg/compare