Template-type: ReDIF-Paper 1.0
Author-Name: Hang K. Ryu
Author-Workplace-Name: Department of Economics, Chung Ang University, Seoul, Korea.
Author-Name: Daniel J. Slottje
Author-Workplace-Name:
 Department of Economics, SMU, Dallas.
Author-Name:
 Michael McAleer
Author-Workplace-Name:
 Department of Quantitative Finance National Tsing Hua University, Taiwan and Econometric Institute Erasmus School of 
	Economics Erasmus University Rotterdam, The Netherlands and Department of Quantitative Economics Complutense University of 
	Madrid, Spain And Institute of Advanced Sciences Yokohama National University, Japan.
Title: A New Inequality Measure that is Sensitive to Extreme Values and Asymmetries
Abstract: There is a vast literature on the selection of an appropriate index of income inequality and on what desirable properties such a 
	measure (or index) should contain. The Gini index is, of course, the most popular. There is a concurrent literature on the use of 
	hypothetical statistical distributions to approximate and describe an observed distribution of incomes. Pareto and others observed 
	early on that incomes tend to be heavily right-tailed in their distribution. These asymmetries led to approximating the observed income 
	distributions with extreme value hypothetical statistical distributions, such as the Pareto distribution. But these income distribution 
	functions (IDFs) continue to be described with a single index (such as the Gini) that poorly detects the extreme values present in the 
	underlying empirical IDF. This paper introduces a new inequality measure to supplement, but not to replace, the Gini that measures more 
	accurately the inherent asymmetries and extreme values that are present in observed income distributions. The new measure is based on a 
	third-order term of a Legendre polynomial from the logarithm of a share function (or Lorenz curve). We advocate using the two measures 
	together to provide a better description of inequality inherent in empirical income distributions with extreme values.
Classification-JEL: D31, D63.
Keywords: Inequality Index, Extreme value distributions, Maximum entropy method, Orthonormal basis, Legendre polynomials.
Length: 35 pages 
Creation-Date: 2017-10
Number: 2017-25
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1725.txt
File-URL: https://eprints.ucm.es/id/eprint/45315/1/1725.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1725