Abstract
This article considers a Mann–Whitney test of distributional effects in a multivalued treatment. Specifically, we first show that, under the unconfoundedness condition, the counterfactual distributions are weighted averages, with weights satisfying some moment restrictions. We estimate the weights directly from those restrictions by maximizing a globally concave objective function and then construct the Mann–Whitney statistics with the estimated distributions. We show that our Mann–Whitney statistics are efficient, attaining the semiparametric efficiency bound which is also derived here. A simulation study and an application to the analysis of racial discrimination illustrate the practical value of the proposed approach.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
