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Wakefield Publishes New Article on Small Area Estimation with Random Forests and the LASSO

Posted: 9/8/2023 (CSDE Research)

CSDE Affiliate Jon Wakefield, along with co-authors, has published new research in arXiv entitled, “Small Area Estimation with Random Forests and the LASSO”. They consider random forests and LASSO methods for model-based small area estimation when the number of areas with sampled data is a small fraction of the total areas for which estimates are required. Abundant auxiliary information is available for the sampled areas, from the survey, and for all areas, from an exterior source, and the goal is to use auxiliary variables to predict the outcome of interest. Among the four modelling methods considered, the Bayesian shrinkage performed the best in terms of bias, MSE and prediction interval coverages and scores, as assessed through a cross-validation study. Excellent work, Dr. Wakefield!