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Concentration Curve and Index×Lorenz Curve×
حوزهاقتصادSociology
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش19911905
پدیدآورAdam Wagstaff, Pierella Paci & Eddy van DoorslaerMax Otto Lorenz
نوعBivariate inequality measureGraphical representation of distributional inequality
منبع بنیادینWagstaff, A., Paci, P., & van Doorslaer, E. (1991). On the measurement of inequalities in health. Social Science & Medicine, 33(5), 545–557. DOI ↗Lorenz, M. O. (1905). Methods of measuring the concentration of wealth. Publications of the American Statistical Association, 9(70), 209–219. DOI ↗
نام‌های دیگرHealth Concentration Index, Concentration Curve, Socioeconomic Inequality in Health Index, Wagstaff IndexLorenz concentration curve, Lorenz diagram, cumulative share curve
مرتبط35
خلاصهThe concentration curve and concentration index, established as the standard tools for measuring socioeconomic inequality in health by Wagstaff, Paci, and van Doorslaer in 1991, capture how a health variable is distributed across the population ranked by socioeconomic status. The concentration curve plots the cumulative share of health (or ill-health) against the cumulative share of people ordered from poorest to richest; the concentration index is twice the area between this curve and the line of equality. Unlike the Gini coefficient, which measures pure dispersion, the concentration index is bivariate — it measures inequality in one variable that is systematically related to a second, socioeconomic ranking.The Lorenz curve is a graphical device that displays the full shape of inequality in a distribution by plotting the cumulative share of a quantity (such as income) held by the cumulative share of the population, ranked from poorest to richest. Introduced by Max Lorenz in 1905, it underlies the Gini coefficient and provides the basis for ranking distributions by inequality when one curve lies entirely above another.
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ScholarGateمقایسهٔ روش‌ها: Concentration Curve and Index · Lorenz Curve. بازیابی‌شده در 2026-06-25 از https://scholargate.app/fa/compare