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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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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.
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.
Substituting X and L(X) to the above equation, and using partial integration concerning,
Received October 12, 1982. Revised April 22, 1983.
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:
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).