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Measuring Health Inequality with Categorical Data: Some Regional Patterns

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  • Joan Costa-i-Font
  • Frank Cowell

Abstract

Much of the theoretical literature on inequality assumes that the equalisand is a cardinal variable like income or wealth. However, health status is generally measured as a categorical variable expressing a qualitative order. Traditional solutions involve reclassifying the variable by means of qualitative models and relying on inequality measures that are mean independent. We argue that the way status is conceptualized has important theoretical implications for measurement as well as for policy analysis. We also bring to the data a recently proposed approach to measuring self-reported health inequality that meets both rigorous and practical considerations. We draw upon the World Health Survey data to examine alternative pragmatic methods for making health inequality comparisons. Findings suggest significant differences in health inequality measurement and that regional and country patterns of inequality orderings do not coincide with any reasonable categorization of countries by health system organization.

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Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 4427.

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Date of creation: 2013
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Handle: RePEc:ces:ceswps:_4427

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Related research

Keywords: health inequality; categorical data; health surveys; upward status; downward status;

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References

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  1. Stevenson, Betsey & Wolfers, Justin, 2008. "Happiness Inequality in the United States," IZA Discussion Papers 3624, Institute for the Study of Labor (IZA).
  2. Naga, Ramses H. Abul & Yalcin, Tarik, 2010. "Median Independent Inequality Orderings," SIRE Discussion Papers 2010-118, Scottish Institute for Research in Economics (SIRE).
  3. Allison, R. Andrew & Foster, James E., 2004. "Measuring health inequality using qualitative data," Journal of Health Economics, Elsevier, vol. 23(3), pages 505-524, May.
  4. Maasoumi, Esfandiar, 1986. "The Measurement and Decomposition of Multi-dimensional Inequality," Econometrica, Econometric Society, vol. 54(4), pages 991-97, July.
  5. Ramses H. Abul Naga & Tarik Yalcin, 2007. "Inequality Measurement forOrdered Response Health Data," STICERD - Distributional Analysis Research Programme Papers 92, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  6. Arie Kapteyn & James P. Smith & Arthur van Soest, 2007. "Vignettes and Self-Reports of Work Disability in the United States and the Netherlands," American Economic Review, American Economic Association, vol. 97(1), pages 461-473, March.
  7. Costa-Font, Joan & Hernández-Quevedo, Cristina, 2012. "Measuring inequalities in health: What do we know? What do we need to know?," Health Policy, Elsevier, vol. 106(2), pages 195-206.
  8. Buhong Zheng, 2011. "A new approach to measure socioeconomic inequality in health," Journal of Economic Inequality, Springer, vol. 9(4), pages 555-577, December.
  9. Nigel Rice & Silvana Robone & Peter Smith, 2009. "Vignettes and health systems responsiveness in crosscountry comparative analyses," Health, Econometrics and Data Group (HEDG) Working Papers 09/29, HEDG, c/o Department of Economics, University of York.
  10. Wagstaff, Adam & Paci, Pierella & van Doorslaer, Eddy, 1991. "On the measurement of inequalities in health," Social Science & Medicine, Elsevier, vol. 33(5), pages 545-557, January.
  11. Doorslaer, Eddy van & Jones, Andrew M., 2003. "Inequalities in self-reported health: validation of a new approach to measurement," Journal of Health Economics, Elsevier, vol. 22(1), pages 61-87, January.
  12. Benedicte Apouey, 2007. "Measuring health polarization with self-assessed health data," Health Economics, John Wiley & Sons, Ltd., vol. 16(9), pages 875-894.
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