השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| עיצוב עקמומיות רגרסיה (RKD)× | שיטת המשתנים המתערבים (IV) להסקה סיבתית× | |
|---|---|---|
| תחום≠ | הסקה סיבתית | כלכלת בריאות |
| משפחה≠ | Regression model | Process / pipeline |
| שנת המקור≠ | 2015 | 1990s (modern applications) |
| הוגה השיטה≠ | Card, Lee, Pei & Weber | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| סוג≠ | Quasi-experimental design (slope-based RDD) | Method |
| מקור מכונן≠ | 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. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| כינויים | RKD, regression kink design, kink regression discontinuity, Regresyon Kırılma Tasarımı (RKD — Regression Kink Design) | IV, two-stage least squares, TSLS, causal estimation |
| קשורות≠ | 4 | 3 |
| תקציר≠ | 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. |
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