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TOPIC:
Non-parametric Estimation and Uniform Inference of Treatment Effects
ABSTRACT
Ai et al. (2021) proposed an estimation of the general treatment model that encompasses binary, multi-valued, continuous, and a mixture of discrete and continuous treatments. They considered parametric treatment effects. This paper extends their results to the nonparametric treatment effects and to the nonparametric heterogeneous treatment effects. Under some sufficient conditions, the paper derives the large sample properties of the proposed estimator and establishes uniform confidence bands.