By Gianni Betti, Achille Lemmi
This impressive collection from a few of today’s prime distributional analysts presents an outline quite a lot of fiscal, statistical and sociological relationships which have been unfolded for clinical examine via the paintings of 2 turn-of-the-20th-century economists: C. Gini and M. O. Lorenz.
The authors contain such figues as Barry Arnold and Frank Cowell and the ensuing e-book merits its position at the bookshelf of significant mathematical economists everywhere.
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Extra resources for Advances on Income Inequality and Concentration Measures
For example, if in our simple example, instead of spending an exp(l) time in each state, the process spends an exp(li) time in state i, i = 1,2, . , n, it is well known that the choice li = l, i = 1,2, . , n results in minimal variability in the sense of Lorenz ordering. In fact, O’Cinneide (1991) has veriﬁed that among all phase type distributions of order n, the simple gamma random variable T* ~ G(n,l) exhibits least variability as measured by the Lorenz order. 2 Connected components of a random graph Following Ross (1981) consider a random graph with nodes 1,2, .
G. Taguchi 1972; Arnold 1983). 3), in terms of the quantile function F −1 X . Such a deﬁnition involves ordering the observations and it appeared that some multivariate version of 22 Introduction either order statistics or the quantile function would be required in order to take Lorenz’s curve successfully to higher dimensions. Instead, the key lay in redeﬁning the Lorenz curve in a manner that did not involve ordering the data. As Lorenz did in the one dimensional case, we begin by considering a ﬁnite population of n individuals.
London: Cambridge University Press. L. J. Slottje (2003) ‘Inequality aversion and the natural rate of subjective inequality’, Journal of Public Economics 87: 1061–90. Lemmi A. A. Cowell, Estimation of Inequality Indices’, in Editors’ introduction 11 Silber, J. ), Handbook on Income Inequality Measurement, Kluwer Academic Publishers: Boston/Dordrecht/London, pp. 286–289. O. (1905). ‘Methods of measuring concentration of wealth’, Journal of the American Statistical Association, 9: 209–219. Maasoumi, E.