avoids a lack of transparency and model overfitting. Our focus is on two-stage estimators: in the first stage, Lasso … estimation is conducted using data on cluster-level averages or sums, and in the second stage, standard ATE estimators are …, asymptotic normality of the ATE estimators, and design-based variance estimation. The nonparametric approach applies to …

scalar or vector-valued covariates due to a slower rate of convergence of the parameter estimators. Yet the suggested change …

vector-valued covariates due to a slower rate of convergence of the parameter estimators. Yet the suggested change point test …

We study the small sample properties of conditional quantile estimators such as classical and IV quantile regression …. First, we propose a higher-order analytical framework for comparing competing estimators in small samples and assessing the … asymptotic linear expansions with nearly optimal rates. Second, we study the higher-order bias of exact quantile estimators up to …

We study the small sample properties of conditional quantile estimators such as classical and IV quantile regression …. First, we propose a higher-order analytical framework for comparing competing estimators in small samples and assessing the … asymptotic linear expansions with nearly optimal rates. Second, we study the higher-order bias of exact quantile estimators up to …