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