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A Comparison of Robust Methods for Pareto Tail Modeling in the Case of Laeken Indicators

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Combining Soft Computing and Statistical Methods in Data Analysis

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 77))

Abstract

The Laeken indicators are a set of indicators for measuring poverty and social cohesion in Europe. However, some of these indicators are highly influenced by outliers in the upper tail of the income distribution. This paper investigates the use of robust Pareto tail modeling to reduce the influence of outlying observations. In a simulation study, different methods are evaluated with respect to their effect on the quintile share ratio and the Gini coefficient.

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Author information

Authors and Affiliations

  1. Department of Statistics and Probability Theory, Vienna University of Technology, Wiedner Hauptstraße 8-10, 1040, Vienna, Austria

    Andreas Alfons, Matthias Templ, Peter Filzmoser & Josef Holzer

  2. Methods Unit, Statistics Austria, Guglgasse 13, 1110, Vienna, Austria

    Matthias Templ

  3. Landesstatistik Steiermark, Hofgasse 13, 8010, Graz, Austria

    Josef Holzer

Authors
  1. Andreas Alfons
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  2. Matthias Templ
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  3. Peter Filzmoser
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  4. Josef Holzer
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Editor information

Editors and Affiliations

  1. Research Unit on Intelligent Data Analysis and Graphical Models, European Centre for Soft Computing Edificio Científico-Tecnológico. 3a Planta, C/ Gonzalo Gutiérrez Quirós s/n, 33600, Mieres, Spain

    Christian Borgelt , Gil González-Rodríguez  & Wolfgang Trutschnig ,  & 

  2. Departamento de Estadística e I.O. y D.M., Universidad de Oviedo, Facultad de Ciencias, C/ Calvo Sotelo s/n, 33007, Oviedo, Spain

    María Asunción Lubiano

  3. Departamento de Estadística e I.O. yD.M., Universidad de Oviedo, Facultad de Ciencias, C/ Calvo Sotelo s/n, 33007, Oviedo, Spain

    María Ángeles Gil

  4. Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447, Warsaw, Poland

    Przemysław Grzegorzewski

  5. Systems Research Institute, Polish Academy of Science, Newelska 6, 01-447, Warsaw, Poland

    Olgierd Hryniewicz

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Alfons, A., Templ, M., Filzmoser, P., Holzer, J. (2010). A Comparison of Robust Methods for Pareto Tail Modeling in the Case of Laeken Indicators. In: Borgelt, C., et al. Combining Soft Computing and Statistical Methods in Data Analysis. Advances in Intelligent and Soft Computing, vol 77. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14746-3_3

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  • DOI: https://doi.org/10.1007/978-3-642-14746-3_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14745-6

  • Online ISBN: 978-3-642-14746-3

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