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| 이질적 처리 효과 회귀 불연속 설계 (HTE-RDD)× | 조건부 분위수 회귀× | |
|---|---|---|
| 분야≠ | 인과추론 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2015 | 1978 |
| 창시자≠ | Dong & Lewbel (2015); Chiang, Hsu & Sasaki (2019) | Koenker & Bassett |
| 유형≠ | Quasi-experimental causal inference with effect heterogeneity | Conditional quantile regression |
| 원전≠ | Dong, Y., & Lewbel, A. (2015). Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models. Review of Economics and Statistics, 97(5), 1081-1092. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| 별칭≠ | HTE-RDD, heterogeneous RDD, subgroup RDD, effect heterogeneity RD | conditional quantile regression, regression quantiles, Kantil Regresyon |
| 관련≠ | 4 | 5 |
| 요약≠ | Heterogeneous Treatment Effect RDD extends the classic regression discontinuity framework to detect and estimate how the causal effect of crossing an assignment cutoff varies across subgroups or along covariates. Rather than reporting a single local average treatment effect at the threshold, HTE-RDD maps how treatment impact differs by individual characteristics, enabling richer policy conclusions about who benefits most or least from a threshold-based intervention. | Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails. |
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