A0440
Title: Quantile-based test for heterogeneous treatment effects
Authors: EunYi Chung - University of Illinois at Urbana Champaign (United States) [presenting]
Mauricio Olivares - University College London (United Kingdom)
Abstract: One way to look at the distributional effects of a policy intervention comprises estimating the quantile treatment effect at different quantiles. We exploit this idea and develop a new permutation test for heterogeneous treatment effects based on a modified quantile process. To establish the asymptotic validity of the test, we transform the test statistic using a martingale transformation so that its limit behavior is distribution-free. Numerical evidence shows our permutation test outmatches other popular quantile-based tests in terms of size and power performance. We discuss a fast implementation algorithm and illustrate our method using experimental data from a welfare reform.
