Salīdzināt metodes

	Diferenču diskontinuitātes dizains	Instrumentālo mainīgo (IV) metode cēloņsakarību noteikšanai
Nozare	Cēloņsakarību secināšana	Veselības ekonomika
Saime	Regression model	Process / pipeline
Izcelsmes gads	2016	1990s (modern applications)
Autors	Grembi, Nannicini & Troiano	Angrist & Pischke (applied econometrics); rooted in econometric theory
Tips	Hybrid quasi-experimental causal design (RDD + DID)	Method
Pirmavots	Grembi, V., Nannicini, T. & Troiano, U. (2016). Do Fiscal Rules Matter? A Difference-in-Discontinuities Design. American Economic Journal: Applied Economics, 8(3), 1-30.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Citi nosaukumi	diff-in-disc, DiD-RDD, Süreksizliklerde Fark (Difference-in-Discontinuities)	IV, two-stage least squares, TSLS, causal estimation
Saistītās	5	3
Kopsavilkums	Difference-in-Discontinuities is a hybrid quasi-experimental design that fuses regression discontinuity (RDD) with difference-in-differences (DID), introduced by Grembi, Nannicini and Troiano (2016). It compares the discontinuity at the same cutoff value across two periods to isolate a causal effect.	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.