Confidence Sets Based on Sparse Estimators Are Necessarily Large

Benedikt Pötscher

MPRA Paper from University Library of Munich, Germany

Abstract: Confidence sets based on sparse estimators are shown to be large compared to more standard confidence sets, demonstrating that sparsity of an estimator comes at a substantial price in terms of the quality of the estimator. The results are set in a general parametric or semiparametric framework.

Keywords: sparse estimator; consistent model selection; post-model-selection estimator; penalized maximum likelihood; confidence set; coverage probability (search for similar items in EconPapers)
JEL-codes: C1 C44 (search for similar items in EconPapers)
Date: 2007-08
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (4)

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https://mpra.ub.uni-muenchen.de/5677/1/MPRA_paper_5677.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/15087/3/MPRA_paper_15087.pdf revised version (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:5677

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