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	Regression Kink Design (RKD)	Metoda zmiennych instrumentalnych (IV) do wnioskowania przyczynowego
Dziedzina	Wnioskowanie przyczynowe	Ekonomika zdrowia
Rodzina	Regression model	Process / pipeline
Rok powstania	2015	1990s (modern applications)
Twórca	Card, Lee, Pei & Weber	Angrist & Pischke (applied econometrics); rooted in econometric theory
Typ	Quasi-experimental design (slope-based RDD)	Method
Źródło pierwotne	Card, D., Lee, D. S., Pei, Z. & Weber, A. (2015). Inference on Causal Effects in a Generalized Regression Kink Design. Econometrica, 83(6), 2453-2483.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Inne nazwy	RKD, regression kink design, kink regression discontinuity, Regresyon Kırılma Tasarımı (RKD — Regression Kink Design)	IV, two-stage least squares, TSLS, causal estimation
Pokrewne	4	3
Podsumowanie	The Regression Kink Design is a quasi-experimental method that estimates a causal effect when a policy rule creates a change in slope (a kink) — rather than a jump — at a known threshold of a running variable. It was formalised as a generalized design by Card, Lee, Pei and Weber (2015) and is the slope-based counterpart of the regression discontinuity design.	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.