Estimation of distributional effects of treatment and control under selection on observables: consistency, weak convergence, and applications
Methodology
2019-04-30 v1
Abstract
In this paper the estimation of the distribution function for potential outcomes to receiving or not receiving a treatment is studied. The approach is based on weighting observed data on the basis on estimated propensity score. A weighted version of empirical process is constructed and its weak convergence to bivariate Gaussian process is established. Results for the estimation of the Average Treatment Effect (ATE) and Quantile Treatment Effect (QTE) are obtained as by-products. Applications to the construction of nonparametric tests for the treatment effect and for the stochastic dominance of the treatment over control are considered, and their finite sample properties and merits are studied via simulation.
Keywords
Cite
@article{arxiv.1904.12159,
title = {Estimation of distributional effects of treatment and control under selection on observables: consistency, weak convergence, and applications},
author = {Pier Luigi Conti and Livia De Giovanni},
journal= {arXiv preprint arXiv:1904.12159},
year = {2019}
}