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Measuring income-related inequalities in health using a parametric dependence function

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  • Quinn C

Abstract

Attention has been given recently to the Concentration Index; specifically, corrected versions have been generated that supersede the original with properties such as transform invariance, reversal invariance and transfer invariance. While previous studies have promoted a transformed or normalised index to overcome these problems, I propose, in this paper, two novel approaches to a direct parametric model for dependence as a measure of inequality in the distributions of health and income. These are the copula and quantile regression using jackknifed samples. As well as accommodating any form of health or income, and being robust to invariance criteria, both methods parameterise the measure of inequality directly, rather than indirectly through functions on one of the marginals. Results from an illustrating example using the Survey of Health, Retirement and Ageing in Europe suggest that such inequality in these countries is not explained well by covariates on age, gender, education and lifestyles.

Suggested Citation

  • Quinn C, 2009. "Measuring income-related inequalities in health using a parametric dependence function," Health, Econometrics and Data Group (HEDG) Working Papers 09/24, HEDG, c/o Department of Economics, University of York.
    • Handle: RePEc:yor:hectdg:09/24
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    References listed on IDEAS

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    1. 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.
    2. Bommier, Antoine & Stecklov, Guy, 2002. "Defining health inequality: why Rawls succeeds where social welfare theory fails," Journal of Health Economics, Elsevier, vol. 21(3), pages 497-513, May.
    3. Wagstaff, Adam, 2009. "Correcting the concentration index: A comment," Journal of Health Economics, Elsevier, vol. 28(2), pages 516-520, March.
    4. Andrew M. Jones & Angel López Nicolás, 2004. "Measurement and explanation of socioeconomic inequality in health with longitudinal data," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 1015-1030, October.
    5. Erreygers, Guido, 2009. "Correcting the Concentration Index: A reply to Wagstaff," Journal of Health Economics, Elsevier, vol. 28(2), pages 521-524, March.
    6. Hollander, Heinz, 2001. "On the validity of utility statements: standard theory versus Duesenberry's," Journal of Economic Behavior & Organization, Elsevier, vol. 45(3), pages 227-249, July.
    7. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    8. Wagstaff, Adam & van Doorslaer, Eddy & Watanabe, Naoko, 2003. "On decomposing the causes of health sector inequalities with an application to malnutrition inequalities in Vietnam," Journal of Econometrics, Elsevier, vol. 112(1), pages 207-223, January.
    9. 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.
    10. Erreygers, Guido, 2009. "Correcting the Concentration Index," Journal of Health Economics, Elsevier, vol. 28(2), pages 504-515, March.
    11. 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.
    12. Adam Wagstaff, 2005. "The bounds of the concentration index when the variable of interest is binary, with an application to immunization inequality," Health Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 429-432, April.
    13. Denuit, Michel & Lambert, Philippe, 2005. "Constraints on concordance measures in bivariate discrete data," Journal of Multivariate Analysis, Elsevier, vol. 93(1), pages 40-57, March.
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    Cited by:

    1. , Stone Center & Yonzan, Nishant, 2020. "Assortative Mating and Labor Income Inequality: Evidence from Fifty Years of Coupling in the U.S," SocArXiv 4whvs, Center for Open Science.

    More about this item

    Keywords

    Health Inequality; Non-Continuous data; Copulas; Quantile Regression;

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • I10 - Health, Education, and Welfare - - Health - - - General

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