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Gini's Concentration Ratio: Formula, Application, and Drewnowski's Index, Study notes of Statistics

The gini's concentration ratio, a measure of inequality in distribution, and its application to life tables. The formula for calculating the gini's concentration ratio is presented, along with its connection to drewnowski's equality index. The document also touches upon the use of numerical quadrature for approximation in the context of life tables.

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A FORMULA OF GINI'S CONCENTRATION RATIO
AND ITS APPLICATION TO LIFE TABLES
Kyo Hanada*
Gini's concentration ratio G is formulated in terms of a cumulative distribu-
tion function. The formula is quite simple and makes it easier to calculate
values, as well as to investigate the usefulness of the ratio. In addition, a kind
of Moment Problem is raised concerning Drewnowski's equality index D which
is defined as D=1-G. An application of the formula to life tables showed that
the index worked effectively as to measure equality of length of life. Numerical
quadrature is briefly discussed for an approximation of the calculation in the use
of life tables.
1. Introduction
The Lorentz curve is widely used in econometrics to express income distribu-
tion in terms of difference between the cumulative amount of income and that of
population. The Gini's concentration ratio which is derived from the Lorentz
curve is the index of inequality in a distribution. General explanation of the curve
and the ratio is written concisely by Kendall and Stuart [3].
Recently, equality in distributions of health related variables is becoming main
concern and there is the need for investigation of the applicability of various in-
dices. Drewnowski [1] proposed to apply the Gini's concentration ratio to measure
inequality existing in the distribution of health indicators, including health resources,
manpower and facilities. Preston et al. [4] applied the ratio to mortality differentials
among social classes. Uemura [6] proposed to apply the ratio to life tables and
expressed the need for further investigation of utilities of the ratio.
2. Formula of Gini's concentration ratio
The Lorentz curve Y=L(X) has the following equations with a parameter t,
where,  f(x)is  a density  function  defined  on  x〓0,  and  μis the  expectation.
The  Gini's  concentration  ratio  G  is  a  ratio  of  the  area  surrounded by Y=
X and Y=L(X)to the area of the triangular Y=X, Y=O and X=1:
Substituting X and L(X) to the above equation, and using partial integration
concerning,
Received October 12, 1982. Revised April 22, 1983.
* The Medical Information System Development Center .
J.Japan Statist.Soc.
Vol.13 No.2 1983 95‑98
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A FORMULA OF GINI'S CONCENTRATION RATIO

AND ITS APPLICATION TO LIFE TABLES

Kyo Hanada*

Gini's concentration ratio G is formulated in terms of a cumulative distribu- tion function. The formula is quite simple and makes it easier to calculate values, as well as to investigate the usefulness of the ratio. In addition, a kind of Moment Problem is raised concerning Drewnowski's equality index D which is defined as D=1-G. An application of the formula to life tables showed that the index worked effectively as to measure equality of length of life. Numerical quadrature is briefly discussed for an approximation of the calculation in the use of life tables.

  1. Introduction The Lorentz curve is widely used in econometrics to express income distribu- tion in terms of difference between the cumulative amount of income and that of

population. The Gini's concentration ratio which is derived from the Lorentz curve is the index of inequality in a distribution. General explanation of the curve and the ratio is written concisely by Kendall and Stuart [3]. Recently, equality in distributions of health related variables is becoming main concern and there is the need for investigation of the applicability of various in- dices. Drewnowski [1] proposed to apply the Gini's concentration ratio to measure inequality existing in the distribution of health indicators, including health resources, manpower and facilities. Preston et al. [4] applied the ratio to mortality differentials among social classes. Uemura [6] proposed to apply the ratio to life tables and expressed the need for further investigation of utilities of the ratio.

  1. Formula of Gini's concentration ratio The Lorentz curve Y=L(X) has the following equations with a parameter t,

Substituting X and L(X) to the above equation, and using partial integration concerning,

Received October 12, 1982. Revised April 22, 1983.

  • The Medical Information System Development Center (^).

96 J. JAPAN STATIST. SOC. Vol. 13 No. 2 1983

we get a simple formula of G, such that,

From this formula, it is reasonable that Drewnowski [1] proposed to use an equality index: D=1-G, in place of G. Transformation of the expectation p leads us to the final formulae:

These equations remind us of a problem which is analogous to the classic " Moment Problem", that is•gWhether the following sequence,

can define the population". In other words, F(x) and dk's are equivalent under some conditions. For general distributions, d's are expressed as:

In the same way, other inequality indices, variance and Theil index, can have the formulae:

  1. Application of Drewnowski's equality index to life tables The function 1-F(x) of the previous section may not be popular in general statistics. However, it is a basic function in life tables. Let x denote the age of death and F(x) be the cumulative distribution function of deaths in life tables, then 1-F(x) is the survival number 1(x). Drewnowski's equality index for measurement of equality of length of life can be calculated from,

98 J. JAPAN STATIST. SOC. Vol. 13 No. 2 1983

Acknowledgement The author is grateful to Mr. K. Uemura for his comments on an earlier draft and for drawing my attention to the subject.

REFERENCES

[1] Drewnowski, J. (1982). Social indicators and their application for measuring the progress of development. Working Group on Indicators for Monitoring and Evaluation of Strategy for Health for All by the Year 2000. World Health Organization. [2] Greville, T. N. E. (1960). Spline functions, interpolation, and numerical quadrature, Math- ematical Methods for Digital Computers. II Ralston, A. and Wilf, H. S. (eds.) Ch. 8. Wiley, New York. [3] Kendall, M. G. and Stuart, A. (1966). The Advanced Theory of Statistics. Vol. 1 46-51. Griffin, London. [4] Preston, S. H., Haines, M. R. and Pamuk, E. (1981). Effects of industrialization and ur- banization on mortality in developed countries, International Population Conference. Inter- national Union for the Scientific Study of Population. [5] Uemura, K. (1979). The 14th Complete Life Tables. Department of Statistics and Informa- tion, Ministry of Health and Welfare of Japanese Government (in Japanese with English summary). [6] Uemura, K. (1982). Measure of health indicators. Unpublished manuscript (in Japanese).