Statistical inference for a finite population mean with machine learning-based imputation for missing survey data / by Mehdi Dagdoug and David Haziza.: CS11-522/2024-1-25E-PDF

"National statistical offices have increasingly adopted machine learning (ML) for its potential to improve survey estimates. ML techniques offer significant advantages, notably the ability to manage high-dimensional data and to capture complex, nonlinear relationships, thereby enhancing the overall quality of survey statistics. In this article, following the approach of Chernozhukov et al. (2018), we describe a double debiased machine learning framework that enables valid statistical inference when imputed estimators are derived from ML procedures. Simulation results suggest that the proposed framework performs well in a wide range of scenarios"--Abstract.

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