Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond

We consider estimating a low-dimensional parameter in an estimating equation involving high-dimensional nuisance functions that depend on the target parameter as an input. A central example is the efficient estimating equation for the (local) quantile treatment effect ((L)QTE) in causal inference, which involves the covariate-conditional cumulative distribution function evaluated at the quantile to be estimated. Existing approaches based on flexibly estimating the nuisances and plugging in the estimates, such as debiased machine learning (DML), require we learn the nuisance at …

beyond causal inference distribution effects equation example function functions inference low machine machine learning quantile treatment