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Visualizing inequality

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  • Eliazar, Iddo

Abstract

The study of socioeconomic inequality is of substantial importance, scientific and general alike. The graphic visualization of inequality is commonly conveyed by Lorenz curves. While Lorenz curves are a highly effective statistical tool for quantifying the distribution of wealth in human societies, they are less effective a tool for the visual depiction of socioeconomic inequality. This paper introduces an alternative to Lorenz curves—the hill curves. On the one hand, the hill curves are a potent scientific tool: they provide detailed scans of the rich–poor gaps in human societies under consideration, and are capable of accommodating infinitely many degrees of freedom. On the other hand, the hill curves are a powerful infographic tool: they visualize inequality in a most vivid and tangible way, with no quantitative skills that are required in order to grasp the visualization. The application of hill curves extends far beyond socioeconomic inequality. Indeed, the hill curves are highly effective ‘hyperspectral’ measures of statistical variability that are applicable in the context of size distributions at large. This paper establishes the notion of hill curves, analyzes them, and describes their application in the context of general size distributions.

Suggested Citation

  • Eliazar, Iddo, 2016. "Visualizing inequality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 66-80.
    • Handle: RePEc:eee:phsmap:v:454:y:2016:i:c:p:66-80
    DOI: 10.1016/j.physa.2016.02.062
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    References listed on IDEAS

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    1. François Bourguignon, 2015. "The Globalization of Inequality," Economics Books, Princeton University Press, edition 1, number 10433.
    2. Cowell, Frank, 2011. "Measuring Inequality," OUP Catalogue, Oxford University Press, edition 3, number 9780199594047, Decembrie.
    3. Atkinson, Anthony B., 2015. "Inequality: what can be done?," LSE Research Online Documents on Economics 101810, London School of Economics and Political Science, LSE Library.
    4. Chakrabarti,Bikas K. & Chakraborti,Anirban & Chakravarty,Satya R. & Chatterjee,Arnab, 2013. "Econophysics of Income and Wealth Distributions," Cambridge Books, Cambridge University Press, number 9781107013445.
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