השוואת שיטות

	תכנון רגרסיה בדידה (RDD)	שיטת המשתנים המתערבים (IV) להסקה סיבתית
תחום	אקונומטריקה	כלכלת בריאות
משפחה	Regression model	Process / pipeline
שנת המקור	2008	1990s (modern applications)
הוגה השיטה	Imbens & Lemieux; Lee & Lemieux (modern practice); Cattaneo, Idrobo & Titiunik	Angrist & Pischke (applied econometrics); rooted in econometric theory
סוג	Quasi-experimental causal design	Method
מקור מכונן	Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
כינויים	RDD, regression discontinuity, sharp regression discontinuity, Regresyon Süreksizliği Tasarımı (RDD)	IV, two-stage least squares, TSLS, causal estimation
קשורות	5	3
תקציר	Regression Discontinuity Design is a quasi-experimental method that estimates a local causal effect around a threshold (cutoff) value, comparing units just below and just above the cutoff as if they were almost randomly assigned. It is the design developed for applied practice by Imbens and Lemieux (2008) and by Lee and Lemieux (2010).	Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes.