Robust estimation in partially nonlinear models

Andrés Muñoz and Daniela Rodriguez ()
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Andrés Muñoz: Instituto Técnologico de Buenos Aires
Daniela Rodriguez: Universidad de Buenos Aires and CONICET

Statistical Methods & Applications, 2023, vol. 32, issue 5, No 2, 1407-1437

Abstract: Abstract This paper introduces a class of robust estimators for the parametric and nonparametric components of the partially nonlinear model. The robust estimators are based on a three-step procedure. We prove that the estimates of the parametric component are root–n consistent and asymptotically normally distributed. Through a Monte Carlo study, we compare the performance of our proposal to that of the classical estimators. We illustrate our procedure with examples.

Keywords: Asymptotic properties; Partly nonlinear models; Rate of convergence; Robust estimation; Smoothing techniques (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10260-023-00705-1

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