← Search

Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data

Yu-Chin Hsu¹; Martin Huber²; Ying‐Ying Lee³; Chu-An Liu⁴

¹ Academia Sinica, National Central University, National Chengchi University, and National Taiwan University · ² University of Fribourg · ³ University of California, Irvine · ⁴ Academia Sinica

Abstract We propose a Cramér–von Mises–type test for testing whether the mean potential outcome given a specific treatment level has a weakly monotonic relationship with the continuous treatment under unconfoundedness. To flexibly control for a possibly high-dimensional set of covariates, our test is based on a double debiased machine learning method. We show that our test controls asymptotic size and is consistent against any fixed alternative. We apply our test to evaluate the Job Corps program and reject a weakly negative relationship between the treatment (hours in academic and vocational training) and labor market performance among relatively low treatment values.

DOI

10.1162/rest_a_01416

Volume

108 (3)

Pages

792-806

Language

en

Export

BibTeX

Sources

openalex crossref