Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Diseño de Diferencias en Discontinuidades× | Método de Variables Instrumentales (VI) para Inferencia Causal× | |
|---|---|---|
| Campo≠ | Inferencia causal | Economía de la salud |
| Familia≠ | Regression model | Process / pipeline |
| Año de origen≠ | 2016 | 1990s (modern applications) |
| Autor original≠ | Grembi, Nannicini & Troiano | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| Tipo≠ | Hybrid quasi-experimental causal design (RDD + DID) | Method |
| Fuente seminal≠ | 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. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| Alias≠ | diff-in-disc, DiD-RDD, Süreksizliklerde Fark (Difference-in-Discontinuities) | IV, two-stage least squares, TSLS, causal estimation |
| Relacionados≠ | 5 | 3 |
| Resumen≠ | 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. |
| ScholarGateConjunto de datos ↗ |
|
|