Additivity and the entropy concept: An axiomatic approach to inequality measurement

By Frank A. Cowell, K. Kuga. 1981

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Citations in the corpus

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices (2018, methodology): “Borrowing insights from the rich body of work on the axiomatic characterization of inequality indices in economics and social science [3, 10, 19, 24, 25, 28, 34], we argue that many axioms satisfied by inequality indices are appealing properties for measures of algorithmic unfairness.”
Statistical Size Distributions in Economics and Actuarial Sciences (2003, background): “0 is a sensitivity parameter giving more and more weight to the small incomes as it increases, and the so-called generalized entropy measures (Cowell and Kuga, 1981) GEu ¼ 1 u(u 1) ð1 0 x E(X ) u 1 " # dF(x), (2:28) where u [ Rn{0, 1}.”
A new model of income distribution: the κ-generalized distribution (2011, unknown): “On the inequality side, the entropy-based measure of inequality proposed by Theil (1967) naturally contributed to the development of a general informationtheoretic approach to the measurement of inequality (Cowell 1980a,b; Cowell and Kuga 1981a,b).”
The Redistributive Effects of Tax Benefit Systems in the Enlarged EU (2010, background): “, Cowell and Kuga (1981). The more positive (negative) is, the more sensitive I is to changes at the top (bottom) of the income distribution.”
Reinterpreting between-group inequality (2008, background): “This class of inequality measures can be neatly decomposed into a between- and withingroup component as follows [6, 11, 14]:”