The Power-law Tail Exponent of Income Distributions

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 minimising 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.

arXiv commentLatex2e v1.6; 8 pages with 3 figures; in press (Physica A)

References in corpus (4)

• Problems with Fitting to the Power-Law Distribution
• Power Law Tails in the Italian Personal Income Distribution
• On fitting the Pareto-Levy distribution to stock market index data: selecting a suitable cutoff value
• Exchanges in complex networks: income and wealth distributions

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