Robust Estimation of Economic Indicators from Survey Samples Based on Pareto Tail Modeling

20 Pages Posted: 18 Jun 2012

See all articles by Andreas Alfons

Andreas Alfons

Katholieke Universiteit Leuven - Faculty of Business and Economics (FBE)

Matthias Templ

Vienna University of Technology

Peter Filzmoser

Vienna University of Technology

Date Written: 2012

Abstract

Motivated by a practical application, this paper investigates robust estimation of economic indicators from survey samples based on a semiparametric Pareto tail model. Economic performance is typically measured by a set of indicators, which are often estimated from survey data – the motivating example being the European indicators on social exclusion and poverty computed from the well known EU-SILC survey. Since economic data typically contain variables with heavily tailed distributions and additional extreme outliers, the idea is to use robust Pareto tail modeling to detect the extreme outliers and reduce their influence on the indicators. In the survey context, however, sample weights need to be considered when modeling the tail with a Pareto distribution such that the true distribution on the population level is accurately reflected. Therefore, the main methodological contribution is to adapt commonly used robust estimators for the parameters of the Pareto distribution to take sample weights into account. The resulting approach for robust estimation of indicators is then evaluated by means of a simulation study and applied in the context of estimating the Gini coefficient from EU-SILC data.

Keywords: EU-SILC, Gini coefficient, Pareto distribution, survey statistics, tail modeling

Suggested Citation

Alfons, Andreas and Templ, Matthias and Filzmoser, Peter, Robust Estimation of Economic Indicators from Survey Samples Based on Pareto Tail Modeling (2012). Available at SSRN: https://ssrn.com/abstract=2086260 or http://dx.doi.org/10.2139/ssrn.2086260

Andreas Alfons (Contact Author)

Katholieke Universiteit Leuven - Faculty of Business and Economics (FBE) ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

Matthias Templ

Vienna University of Technology ( email )

Karlsplatz 13
Vienna
Austria

Peter Filzmoser

Vienna University of Technology ( email )

Wien 1040
Austria

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