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| 인과 추론을 위한 위약 검증× | 불연속 차이 설계 (Difference-in-Discontinuities Design)× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2010 | 2016 |
| 창시자≠ | Abadie, Diamond & Hainmueller (synthetic control placebos); Imbens & Lemieux (RDD validity) | Grembi, Nannicini & Troiano |
| 유형≠ | Falsification / robustness test family for causal inference | Hybrid quasi-experimental causal design (RDD + DID) |
| 원전≠ | Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. DOI ↗ | 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 ↗ |
| 별칭≠ | falsification tests, placebo checks, refutation tests, Plasebo Testleri — Nedensel Çıkarım Doğrulama | diff-in-disc, DiD-RDD, Süreksizliklerde Fark (Difference-in-Discontinuities) |
| 관련 | 5 | 5 |
| 요약≠ | Placebo tests are a family of falsification checks that probe the credibility of a causal claim by re-running the analysis on a fake treatment, a false intervention date, or an outcome that should not have been affected. The approach was popularised through the synthetic control work of Abadie, Diamond and Hainmueller (2010) and the regression-discontinuity validity checks of Imbens and Lemieux (2008). | 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. |
| ScholarGate데이터셋 ↗ |
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