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A review of more than one hundred Pareto-tail index estimators

Igor Fedotenkov

MPRA Paper from University Library of Munich, Germany

Abstract: This paper reviews more than one hundred Pareto (and equivalent) tail index estimators. It focuses on univariate estimators for nontruncated data. We discuss basic ideas of these estimators and provide their analytical expressions. As samples from heavy-tailed distributions are analysed by researchers from various fields of science, the paper provides nontechnical explanations of the methods, which could be understood by researchers with intermediate skills in statistics. We also discuss strengths and weaknesses of the estimators, if they are known. The paper can be viewed as a catalog or a reference book on Pareto-tail index estimators.

Keywords: Heavy tails; Pareto distribution; tail index; review; extreme value index (search for similar items in EconPapers)
JEL-codes: C13 C14 C18 C58 (search for similar items in EconPapers)
Date: 2018-11-15
New Economics Papers: this item is included in nep-ecm
References: Add references at CitEc
Citations: View citations in EconPapers (9)

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https://mpra.ub.uni-muenchen.de/90072/1/MPRA_paper_90072.pdf original version (application/pdf)

Related works:
Journal Article: A Review of More than One Hundred Pareto-Tail Index Estimators (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:90072

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