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Measuring Health Inequality in US: A Composite Index Approach

Author

Listed:
  • Raffaele Lagravinese

    (University of Bari “Aldo Moro”)

  • Paolo Liberati

    (Roma Tre University)

  • Giuliano Resce

    (Italian National Research Council of Italy (CNR))

Abstract

In this paper, we use the standardized mortality rates for 21 mutual exclusive causes of death to propose a composite index of US county-level health performances in 1980–2014 interval. We aggregate mortality rates by the stochastic multi-criteria acceptability analysis (SMAA), in order to avoid any a priori judgement on the importance given to a specific cause of death. The total observed inequality among counties is then decomposed to estimate the variability between and within states by means of the Theil index on SMAA outcomes. On average, there has been a decrease in the Composite Index of mortality from 1980 to 2014, but while the majority of counties had an increase in health conditions, some counties have shown a decrease in health performances in the same interval. This may be the reason of a persistent increase of total inequality among counties, with inequality within states constantly higher than inequality between states, both responsible of the growing inequality levels of health performances in the period analysed.

Suggested Citation

  • Raffaele Lagravinese & Paolo Liberati & Giuliano Resce, 2020. "Measuring Health Inequality in US: A Composite Index Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(3), pages 921-946, February.
  • Handle: RePEc:spr:soinre:v:147:y:2020:i:3:d:10.1007_s11205-019-02177-x
    DOI: 10.1007/s11205-019-02177-x
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    More about this item

    Keywords

    Health inequality; Spatial inequality; Stochastic multi-criteria acceptability analysis; Mortality; Composite indicators;
    All these keywords.

    JEL classification:

    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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