Density Deconvolution with Laplace Errors and Unknown Variance

Jun Cai (), William C. Horrace () and Christopher Parmeter
Additional contact information
Jun Cai: Center for Policy Research, Maxwell School, Syracuse University, 426 Eggers Hall, Syracuse, NY 13244, https://www.maxwell.syr.edu/research/center-for-policy-research
William C. Horrace: Center for Policy Research, Maxwell School, Syracuse University, 426 Eggers Hall, Syracuse, NY 13244, https://www.maxwell.syr.edu/directory/william-c-horrace

No 225, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: We consider density deconvolution with zero-mean Laplace errors in the context of an error component regression model. We adapt the minimax deconvolution methods of Meister (2006) to allow for unknown variance of the Laplace errors. We propose a semi-uniformly consistent deconvolution estimator for an ordinary smooth target density and a modified “variance truncation device" for the unknown Laplace error variance. We provide practical guidance for the choice of smoothness parameters of the target density. A simulation study and applications to a stochastic frontier model of US banks and a statistical measurement error model of daily saturated fat intake are provided.

Keywords: Efficiency Estimation; Laplace Distribution; Stochastic Frontier (search for similar items in EconPapers)
JEL-codes: C12 C14 C44 D24 (search for similar items in EconPapers)
Pages: 57 pages
Date: 2020-03
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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https://surface.syr.edu/cpr/257/ (application/pdf)

Related works:
Journal Article: Density deconvolution with Laplace errors and unknown variance (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:max:cprwps:225

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