NDLI: Heavy tailed capital incomes: Zenga index, statistical inference, and ECHP data analysis

Content Provider	Springer Nature Link
Author	Greselin, Francesca Pasquazzi, Leo Zitikis, Ričardas
Copyright Year	2013
Abstract	Micro-data of European Union (EU) countries show that capital incomes account for a large part of disparity in populations and follow heavy-tailed distributions in many EU countries. Measuring and comparing the disparity requires incorporating the relative nature of ‘small’ and ‘large,’ and for this reason we employ the newly developed Zenga index of economic inequality. Its non-parametric estimator does not fall into any well known class of statistics. This makes the development of statistical inference a challenge even for light-tailed populations, let alone heavy-tailed ones, as is the case with capital incomes. In this paper we construct a heavy-tailed Zenga estimator, establish its asymptotic distribution, and derive confidence intervals. We explore the performance of the confidence intervals in a simulation study and draw conclusions about capital incomes in EU countries, based on the 2001 wave of the European Community Household Panel (ECHP) survey.
Starting Page	127
Ending Page	155
Page Count	29
File Format	PDF
ISSN	13861999
Journal	Extremes
Volume Number	17
Issue Number	1
e-ISSN	1572915X
Language	English
Publisher	Springer US
Publisher Date	2013-10-30
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Heavy-tailed populations Statistics of extremes Zenga index Semiparametric estimation Statistics Quality Control, Reliability, Safety and Risk Civil Engineering Hydrogeology Environmental Management Statistics for Business/Economics/Mathematical Finance/Insurance
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Economics, Econometrics and Finance Engineering

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