Correcting the Bias in the Concentration Index when Income is Grouped
AbstractThe problem introduced by grouping income data when measuring socioeconomic inequalities in health (and health care) has been highlighted in a recent study. We reexamine this issue and show there is a tendency to underestimate the concentration index at an increasing rate when lowering the number of income categories. This bias results from a form of measurement error and we propose two correction methods. Firstly, the use of instrumental variables (IV) can reduce the error within income categories. Secondly, through a simple formula for correction that is based only on the number of groups. We compare the performance of these methods using data from 15 European countries and the United States. We find that the simple correction formula reduces the impact of grouping and always outperforms the IV approach. Use of this correction can substantially improve comparisons of the concentration index both across countries and across time.
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Bibliographic InfoPaper provided by Centre for Economic Policy Research, Research School of Economics, Australian National University in its series CEPR Discussion Papers with number 599.
Date of creation: Jan 2009
Date of revision:
concentration index; errors-in-variables; instrumental variables; categorical data; first-order correction;
Find related papers by JEL classification:
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
- I19 - Health, Education, and Welfare - - Health - - - Other
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-04-13 (All new papers)
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