Penalized Likelihood Inference with Survey Data

Joann Jasiak and Purevdorj Tuvaandorj

Papers from arXiv.org

Abstract: This paper extends three Lasso inferential methods, Debiased Lasso, $C(\alpha)$ and Selective Inference to a survey environment. We establish the asymptotic validity of the inference procedures in generalized linear models with survey weights and/or heteroskedasticity. Moreover, we generalize the methods to inference on nonlinear parameter functions e.g. the average marginal effect in survey logit models. We illustrate the effectiveness of the approach in simulated data and Canadian Internet Use Survey 2020 data.

Date: 2023-04
New Economics Papers: this item is included in nep-dcm and nep-ecm
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