Inequality: Methods and Tools

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A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices (2018, background): “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.”
Is It All About the Tails? The Palma Measure of Income Inequality (2013, unknown): “Litchfield (1999) expresses these as follows:2 some high-income countries in particular.”
Inequality, credit and financial crises (2016, background): “Generally speaking, a major concern when studying the effects of inequality is the dependence of outcomes on the specific measure of inequality employed (Litchfield, 1999).”
Accounting for the Recent Decline in Global Income Inequality1 (2004, background): “Income is measured as gross domestic product (GDP) per capita, calibrated across countries with purchasing power parity (PPP) converters, and expressed in constant 1996 U.S. dollars. effect (Litchfield 1999).”
Disproportionality Measures of Concentration, Specialization, and Localization (2008, methodology): “In contrast to the RMD, the GE measures can be derived from a set of axioms that define several useful properties (see, e.g., Cowell 1995; Litchfield 1999).”