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The Power-law Tail Exponent of Income Distributions

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Author Info
F. Clementi
T. Di Matteo
M. Gallegati

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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.

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File URL: http://arxiv.org/abs/physics/0603061
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File URL: http://arxiv.org/pdf/physics/0603061
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Publisher Info
Paper provided by arXiv.org in its series Quantitative Finance Papers with number physics/0603061.

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Date of creation: Mar 2006
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Publication status: Published in Physica A: Statistical and Theoretical Physics, Vol: 370, Issue 1, October 1, 2006, pp. 49-53
Handle: RePEc:arx:papers:physics/0603061

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  1. Olivier V. Pictet & Michel M. Dacorogna & Ulrich A. Muller, 1996. "Hill, Bootstrap and Jackknife Estimators for Heavy Tails," Working Papers 1996-12-10, Olsen and Associates. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Victor M. Yakovenko & J. Barkley Rosser, 2009. "Colloquium: Statistical Mechanics of Money, Wealth, and Income," Quantitative Finance Papers 0905.1518, arXiv.org. [Downloadable!]
  2. C. Guilmi & F. Clementi & T. Matteo & M. Gallegati, 2008. "Social networks and labour productivity in Europe: an empirical investigation," Journal of Economic Interaction and Coordination, Springer, vol. 3(1), pages 43-57, June. [Downloadable!] (restricted)
  3. Zoltan Kuscsik & Denis Horvath, 2007. "Statistical properties of agent-based market area model," Quantitative Finance Papers 0710.0459, arXiv.org. [Downloadable!]
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This page was last updated on 2009-12-15.

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