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Calculating the concentration index when income is grouped

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  • Clarke, Philip
  • Van Ourti, Tom

Abstract

The problem introduced by grouping income data when measuring socioeconomic inequalities in health (and health care) has been highlighted in a recent study in this journal. We re-examine 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 tendency arises due to 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 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.

Suggested Citation

  • Clarke, Philip & Van Ourti, Tom, 2010. "Calculating the concentration index when income is grouped," Journal of Health Economics, Elsevier, vol. 29(1), pages 151-157, January.
  • Handle: RePEc:eee:jhecon:v:29:y:2010:i:1:p:151-157
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    References listed on IDEAS

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    Cited by:

    1. Guido Erreygers & Philip Clarke & Qiong Zheng, 2017. "On the measurement of socioeconomic inequality of health between countries," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(2), pages 175-193, June.
    2. Erreygers, Guido & Clarke, Philip & Van Ourti, Tom, 2012. "“Mirror, mirror, on the wall, who in this land is fairest of all?”—Distributional sensitivity in the measurement of socioeconomic inequality of health," Journal of Health Economics, Elsevier, vol. 31(1), pages 257-270.
    3. Mototsugu Fukushige & Noriko Ishikawa & Satoko Maekawa, 2012. "A modified Kakwani measure for health inequality," Health Economics Review, Springer, vol. 2(1), pages 1-7, December.

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