مقایسهٔ روش‌ها

	طرح ناپیوستگی رگرسیون فضایی (Spatial RDD)	رگرسیون فازی ناپیوستگی (Fuzzy Regression Discontinuity Design)
حوزه	استنتاج علّی	استنتاج علّی
خانواده	Regression model	Regression model
سال پیدایش	2010s	2001
پدیدآور	Popularized by Dell (2010); formalized for geographic boundaries by Keele & Titiunik (2015)	Hahn, Todd & van der Klaauw
نوع	Quasi-experimental causal inference	Quasi-experimental causal inference
منبع بنیادین	Dell, M. (2010). The Persistent Effects of Peru's Mining Mita. Econometrica, 78(6), 1863-1903.	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	Spatial RDD, Geographic RDD, Border RD Design, Geographic Discontinuity Design	Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
مرتبط	4	5
خلاصه	Spatial Regression Discontinuity Design uses a geographic or administrative boundary as the threshold that assigns units to treatment. Observations just inside one side of the boundary are compared with those just outside it, exploiting the near-random variation in treatment status near the cutoff to recover a local causal effect. The approach is widely used in economics, political science, and public health when policies or institutions change sharply at a border.	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.