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| Thiết kế Gián đoạn Hồi quy (Regression Discontinuity Design - RDD)× | Biến công cụ thông qua Bình phương tối thiểu hai giai đoạn (IV/2SLS)× | |
|---|---|---|
| Lĩnh vực | Suy luận nhân quả | Suy luận nhân quả |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 2008 | 2009 |
| Người khởi xướng≠ | Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction) | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) |
| Loại≠ | Quasi-experimental causal design | Instrumental-variables regression |
| Công trình gốc≠ | Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗ | Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Tên gọi khác | RDD, regression discontinuity design, sharp RDD, fuzzy RDD | instrumental variables, IV estimation, 2SLS, instrumental variable regression |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold. | IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009). |
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