Confidence Sets Based on Sparse Estimators Are Necessarily Large

Pötscher, Benedikt M. (2007): Confidence Sets Based on Sparse Estimators Are Necessarily Large.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: sparse estimator, consistent model selection, post-model-selection estimator, penalized maximum likelihood, confidence set, coverage probability
• Subjects: C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C44 - Operations Research ; Statistical Decision Theory; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General

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