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Calculating the concentration index when income is grouped
1School of Public Health, The University of Sydney, Edward Ford Building (A27), New South Wales 2006, Australia. philipc@health.usyd.edu.au
Journal of Health Economics
|January 12, 2010
Summary
Grouping income data for health inequality studies can underestimate the concentration index. A simple correction formula effectively addresses this measurement error, improving cross-country and temporal comparisons of health equity.
Area of Science:
- Health Economics
- Biostatistics
- Social Epidemiology
Background:
- Socioeconomic inequalities in health are often measured using income data.
- Grouping income categories can introduce measurement error, potentially biasing inequality estimates.
Purpose of the Study:
- To re-examine the impact of income data grouping on the measurement of socioeconomic inequalities in health.
- To propose and evaluate methods for correcting the underestimation of the concentration index caused by data grouping.
Main Methods:
- Re-examination of the concentration index calculation with varying numbers of income categories.
- Application of instrumental variables (IV) as a correction method.
- Development and application of a simple correction formula based on the number of income groups.
Main Results:
- Lowering the number of income categories leads to an increasing underestimation of the concentration index.
- The simple correction formula effectively reduces the impact of income data grouping.
- The simple correction formula consistently outperforms the instrumental variables (IV) approach.
Conclusions:
- A simple correction formula can significantly improve the accuracy of concentration index calculations.
- Accurate measurement of health inequalities is crucial for reliable cross-country and temporal comparisons.
- Addressing data grouping issues enhances the validity of socioeconomic health inequality research.
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