مقایسهٔ روش‌ها

	ناپیوستگی رگرسیون فازی برای ارزیابی سیاست	رگرسیون فازی ناپیوستگی (Fuzzy Regression Discontinuity Design)
حوزه	استنتاج علّی	استنتاج علّی
خانواده	Regression model	Regression model
سال پیدایش	2001	2001
پدیدآور	Hahn, Todd & Van der Klaauw	Hahn, Todd & van der Klaauw
نوع	Quasi-experimental / local IV estimator	Quasi-experimental causal inference
منبع بنیادین	Hahn, 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.	Hahn, 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.
نام‌های دیگر	Fuzzy RDD, Fuzzy RD, Fuzzy Regression Discontinuity, Imperfect Compliance RDD	Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
مرتبط	5	5
خلاصه	Fuzzy 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.	Fuzzy Regression Discontinuity Design (Fuzzy RDD) estimates causal effects when eligibility for a treatment is determined by a threshold on a running variable but actual take-up of that treatment is imperfect — some eligible units do not receive treatment and some ineligible units do. The cutoff acts as an instrument, and the estimand is a Local Average Treatment Effect (LATE) for compliers near the threshold.