So sánh phương pháp

	Thiết kế Hồi quy Gián đoạn Đánh giá Chính sách	Thiết kế gián đoạn hồi quy mờ
Lĩnh vực	Suy luận nhân quả	Suy luận nhân quả
Họ	Regression model	Regression model
Năm ra đời	1960; policy evaluation applications widespread from 2000s	2001
Người khởi xướng	Thistlethwaite & Campbell (1960); popularized in policy evaluation by Lee & Lemieux (2010)	Hahn, Todd & van der Klaauw
Loại	Quasi-experimental causal design	Quasi-experimental causal inference
Công trình gốc	Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355.	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.
Tên gọi khác	Policy RDD, RD design in policy evaluation, regression discontinuity policy analysis, RDD policy impact	Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
Liên quan	5	5
Tóm tắt	Policy Evaluation Regression Discontinuity Design (Policy RDD) exploits a known eligibility threshold in a policy rule to estimate the causal effect of that policy on outcomes. Units just below the cutoff serve as a credible comparison group for units just above it, making RDD one of the most transparent quasi-experimental strategies for assessing what a policy actually achieves.	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.