Standardizing the design lets debiased lasso inference remain asymptotically valid under finite moments, dependent errors, heteroskedasticity, and mild misspecification, at the cost of stricter sparsity.
Inference on treatment effects after selection among high-dimensional controls†.The Review of Economic Studies, 81(2):608–650, 04 2014
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Debiasing the Lasso under Weaker Tail Assumptions
Standardizing the design lets debiased lasso inference remain asymptotically valid under finite moments, dependent errors, heteroskedasticity, and mild misspecification, at the cost of stricter sparsity.