Towards a General Large Sample Theory for Regularized Estimators

Michael Jansson and Demian Pouzo

Papers from arXiv.org

Abstract: We present a general framework for studying regularized estimators; such estimators are pervasive in estimation problems wherein "plug-in" type estimators are either ill-defined or ill-behaved. Within this framework, we derive, under primitive conditions, consistency and a generalization of the asymptotic linearity property. We also provide data-driven methods for choosing tuning parameters that, under some conditions, achieve the aforementioned properties. We illustrate the scope of our approach by presenting a wide range of applications.

Date: 2017-12, Revised 2020-07
New Economics Papers: this item is included in nep-big and nep-ecm
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http://arxiv.org/pdf/1712.07248 Latest version (application/pdf)

Related works:
Working Paper: Towards a general large sample theory for regularized estimators (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1712.07248

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