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| Robust Regression Discontinuity Design× | Metoda różnic w różnicach (Diff-in-Diff)× | |
|---|---|---|
| Dziedzina≠ | Wnioskowanie przyczynowe | Ekonometria |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 2014 | 1994 |
| Twórca≠ | Calonico, Cattaneo & Titiunik | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Typ≠ | Quasi-experimental causal inference | Causal inference / panel regression |
| Źródło pierwotne≠ | Calonico, S., Cattaneo, M. D., & Titiunik, R. (2014). Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs. Econometrica, 82(6), 2295-2326. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Inne nazwy≠ | Robust RDD, Bias-corrected RDD, CCT estimator, rdrobust | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Pokrewne≠ | 4 | 5 |
| Podsumowanie≠ | Robust RDD extends the classical regression discontinuity design with bias correction and robust confidence intervals, addressing the under-coverage problem of conventional RDD inference. Developed by Calonico, Cattaneo, and Titiunik (2014), it uses local polynomial estimation with a bias-corrected point estimate and a wider variance term that accounts for the added uncertainty, yielding confidence intervals with correct asymptotic coverage. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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