Comparer des méthodes

	Regression Discontinue à Effet Hétérogène avec Variable Instrumentale	Régression quantile
Domaine	Inférence causale	Économétrie
Famille	Regression model	Regression model
Année d'origine	2001	1978
Auteur d'origine	Hahn, Todd & Van der Klaauw (2001); extensions by Calonico, Cattaneo & Titiunik (2014)	Koenker & Bassett
Type	Quasi-experimental causal inference / heterogeneity analysis	Conditional quantile regression
Source fondatrice	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.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Alias	HTE-Fuzzy RDD, heterogeneous LATE at threshold, subgroup fuzzy RD, fuzzy RD with effect heterogeneity	conditional quantile regression, regression quantiles, Kantil Regresyon
Apparentées	5	5
Résumé	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.