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| 이질적 처리 효과 퍼지 회귀 불연속× | 조건부 분위수 회귀× | |
|---|---|---|
| 분야≠ | 인과추론 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2001 | 1978 |
| 창시자≠ | Hahn, Todd & Van der Klaauw (2001); extensions by Calonico, Cattaneo & Titiunik (2014) | Koenker & Bassett |
| 유형≠ | Quasi-experimental causal inference / heterogeneity analysis | Conditional quantile regression |
| 원전≠ | Hahn, J., Todd, P., & Van der Klaauw, W. (2001). Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design. Econometrica, 69(1), 201-209. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| 별칭≠ | HTE-Fuzzy RDD, heterogeneous LATE at threshold, subgroup fuzzy RD, fuzzy RD with effect heterogeneity | conditional quantile regression, regression quantiles, Kantil Regresyon |
| 관련 | 5 | 5 |
| 요약≠ | Heterogeneous Treatment Effect Fuzzy RDD extends the standard fuzzy regression discontinuity design — where treatment probability, not treatment status itself, jumps at a threshold — by examining whether the Local Average Treatment Effect (LATE) estimated at the threshold differs systematically across subgroups defined by covariates such as gender, socioeconomic status, or prior ability. It combines the instrumental-variable logic of fuzzy RDD with structured heterogeneity analysis. | 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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