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What is Learnable in Valiant's Theory of the Learnable? 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Debiased Inference of Average Partial Effects in Single-Index Models
David A. Hirshberg, Stefan Wager · 2018-11-07 · via math.ST updates on arXiv.org

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.

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