Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
Singapore Management University
Average treatment effect;High dimension;Least absolute shrinkage and selection operator (Lasso);Nonparametric quantile regression;Nonseparable models;Quantile treatment effect;Unconditional average structural derivative
Articles 1 - 1 of 1
Full-Text Articles in Social and Behavioral Sciences
Non-Separable Models With High-Dimensional Data, Liangjun Su, T Ura, Yc Zhang
Non-Separable Models With High-Dimensional Data, Liangjun Su, T Ura, Yc Zhang
Research Collection School Of Economics
This paper studies non-separable models with a continuous treatment when the dimension of the control variables is high and potentially larger than the effective sample size. We propose a three-step estimation procedure to estimate the average, quantile, and marginal treatment effects. In the first stage we estimate the conditional mean, distribution, and density objects by penalized local least squares, penalized local maximum likelihood estimation, and numerical differentiation, respectively, where control variables are selected via a localized method of L-1-penalization at each value of the continuous treatment. In the second stage we estimate the average and marginal distribution of the potential …