Debiased Inference of Average Partial Effects in Single-Index Models
arXiv:1811.02547
Abstract
We propose a method for average partial effect estimation in high-dimensional single-index models that is root-n-consistent and asymptotically unbiased given sparsity assumptions on the underlying regression model. This note was prepared as a comment on Wooldridge and Zhu [2018], forthcoming in the Journal of Business and Economic Statistics.