Statistical Inference for a Finite Population Mean with Machine Learning-Based Imputation for Missing Survey Data
Articles and reports: 11-522-X202500100025Description: 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.
Issue Number: 2025001Author(s): Haziza, David; Dagdoug, MehdiMain Product:Statistics Canada International Symposium Series: Proceedings
