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The Power-law Tail Exponent of Income Distributions

Clementi, Fabio; Di Matteo, Tiziana; Gallegati, M

Description

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.

CollectionsANU Research Publications
Date published: 2006
Type: Journal article
URI: http://hdl.handle.net/1885/85072
Source: Physica A: Statistical mechanics and its applications
DOI: 10.1016/j.physa.2006.04.027

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