Linganisha mbinu

	Heterogeneous Treatment Effect Regression Discontinuity Design	Regression ya Kiasi (Quantile Regression)
Nyanja	Uhitimisho wa Kisababishi	Ekonometriki
Familia	Regression model	Regression model
Mwaka wa asili	2015	1978
Mwanzilishi	Dong & Lewbel (2015); Chiang, Hsu & Sasaki (2019)	Koenker & Bassett
Aina	Quasi-experimental causal inference with effect heterogeneity	Conditional quantile regression
Chanzo asilia	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.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Majina mbadala	HTE-RDD, heterogeneous RDD, subgroup RDD, effect heterogeneity RD	conditional quantile regression, regression quantiles, Kantil Regresyon
Zinazohusiana	4	5
Muhtasari	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.