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Related Experiment Videos

Measuring inequality: tools and an illustration.

Ruth F G Williams1, D P Doessel

  • 1School of Applied Economics, and Centre for Strategic Economic Studies, Victoria University, Melbourne, Australia. ruth.williams@vu.edu.au

International Journal for Equity in Health
|May 24, 2006
PubMed
Summary

Common health inequality measures can be misleading. Different measurement tools yield varied rankings of health service distributions, impacting social welfare assessments.

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Area of Science:

  • Health economics
  • Social epidemiology

Background:

  • Commonly used measures for health inequality can obscure the complexity of ranking distributions.
  • The underlying social welfare function is crucial for interpreting inequality measures.

Purpose of the Study:

  • To demonstrate how different inequality measures have varying implications for societal welfare.
  • To highlight the importance of understanding economic theory in health equity analysis.

Main Methods:

  • Applied various distribution measurement tools to illustrative data on mental health services.
  • Utilized conventional dispersion measures (e.g., standard deviation, Gini coefficient) and less common ones (e.g., Theil's Index, Atkinson's Measure).
  • Included Lorenz curves for visual representation of distributions.

Main Results:

  • Rankings of health service distributions differ based on the inequality measure employed.
  • Illustrates the sensitivity of inequality assessment to the chosen methodology.

Conclusions:

  • Economic literature on inequality and inequity may be underutilized in health equity research.
  • Understanding economic principles enhances the analysis of health inequalities and inequities.

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