Double/Debiased Machine Learning

A method at the intersection of econometrics and statistics that constructs estimation equations that are Neyman-orthogonal with respect to nuisance parameters, reducing bias in target parameter estimation from linear to quadratic dependence. This allows nuisance parameters to converge at slower rates while the target parameter still achieves parametric convergence rates.