#9923. Density deconvolution with Laplace errors and unknown variance

September 2026publication date
Proposal available till 25-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Social Sciences (miscellaneous);
Economics and Econometrics;
Business and International Management;
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
We consider density deconvolution with zero-mean Laplace noise in the context of an error component regression model. We adapt the minimax deconvolution methods of Meister (20XX) to allow estimation of the unknown noise variance. We propose a semi-uniformly consistent estimator for an ordinary-smooth target density and a modified variance truncation device” for the unknown noise variance. We provide a simulation study and practical guidance for the choice of smoothness parameters of the ordinary-smooth target density. We apply restricted versions of our estimator to a stochastic frontier model of US banks and to a measurement error model of daily saturated fat intake.
Keywords:
Ordinary smooth; Semi-parametric; Stochastic frontier

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