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The Power-law Tail Exponent of Income Distributions

Date

Authors

Clementi, Fabio

Di Matteo, Tiziana

Gallegati, M

Publisher

Elsevier

Abstract

In this paper we tackle the problem of estimating the power-law tail exponent of income distributions by using the Hill's estimator. A subsample semi-parametric bootstrap procedure minimizing the mean squared error is used to choose the power-law cutoff value optimally. This technique is applied to personal income data for Australia and Italy.

Keywords

Keywords: Finance; Method of moments; Optimization; Pareto principle; Problem solving; Sampling; Bootstrap; Hill's estimator; Pareto's index; Personal income; Financial data processing Bootstrap; Hill's estimator; Pareto's index; Personal income

URI

http://hdl.handle.net/1885/85072

Collections

ANU Research Publications

Source

Physica A: Statistical mechanics and its applications

Type

Journal article

DOI

10.1016/j.physa.2006.04.027

Restricted until

2037-12-31

Downloads

File

Description

01_Clementi_The_Power-law_Tail_Exponent_of_2006.pdf (731.89 KB)