One-Step Robust Estimation of Fixed-Effects Panel Data Models

M. Aquaro, P. Cizek

Research output: Working paperDiscussion paperOther research output

Abstract

The panel-data regression models are frequently applied to micro-level data, which often suffer from data contamination, erroneous observations, or unobserved heterogeneity. Despite the adverse effects of outliers on classical estimation methods, there are only a few robust estimation methods available for fixed-effect panel data. Aiming at estimation under weak moment conditions, a new estimation approach based on two different data transformation is proposed. Considering several robust estimation methods applied on the transformed data, we derive the finite-sample, robust, and asymptotic properties of the proposed estimators including their breakdown points and asymptotic distribution. The finite-sample performance of the existing and proposed methods is compared by means of Monte Carlo simulations.
Original languageEnglish
Place of PublicationTilburg
PublisherEconometrics
Number of pages28
Volume2010-110
Publication statusPublished - 2010

Publication series

NameCentER Discussion Paper
Volume2010-110

Keywords

  • breakdown point
  • fixed effects
  • panel data
  • robust estimation

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