IDEAS home Printed from https://ideas.repec.org/p/yor/hectdg/09-24.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.york.ac.uk/media/economics/documents/herc/wp/09_24.pdf
    File Function: Main text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    4. Erreygers, Guido, 2009. "Correcting the Concentration Index: A reply to Wagstaff," Journal of Health Economics, Elsevier, vol. 28(2), pages 521-524, March.
    5. 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.
    6. 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.
    7. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, October.
    8. 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.
    9. 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.
    10. Wagstaff, Adam, 2009. "Correcting the concentration index: A comment," Journal of Health Economics, Elsevier, vol. 28(2), pages 516-520, March.
    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. Erreygers, Guido, 2009. "Correcting the Concentration Index," Journal of Health Economics, Elsevier, vol. 28(2), pages 504-515, March.
    13. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Erreygers, Guido & Van Ourti, Tom, 2011. "Measuring socioeconomic inequality in health, health care and health financing by means of rank-dependent indices: A recipe for good practice," Journal of Health Economics, Elsevier, vol. 30(4), pages 685-694, July.
    2. FLEURBAEY, Marc & SCHOKKAERT, Erik, 2011. "Equity in health and health care," LIDAM Discussion Papers CORE 2011026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Baeten, Steef & Van Ourti, Tom & van Doorslaer, Eddy, 2013. "Rising inequalities in income and health in China: Who is left behind?," Journal of Health Economics, Elsevier, vol. 32(6), pages 1214-1229.
    4. 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.
    5. Buhong Zheng, 2011. "A new approach to measure socioeconomic inequality in health," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(4), pages 555-577, December.
    6. H. Eme Ichoku & William Fonta & Michael Thiede, 2011. "Socioeconomic gradients in self-rated health: a developing country case study of Enugu State, Nigeria," Economic Change and Restructuring, Springer, vol. 44(3), pages 179-202, August.
    7. Zhong, Hai, 2009. "A multivariate analysis of the distribution of individual's welfare in China: What is the role of health?," Journal of Health Economics, Elsevier, vol. 28(6), pages 1062-1070, December.
    8. Aristides dos Santos, Anderson Moreira & Perelman, Julian & Jacinto, Paulo de Andrade & Tejada, Cesar Augusto Oviedo & Barros, Aluísio J.D. & Bertoldi, Andréa D. & Matijasevich, Alicia & Santos, Iná S, 2019. "Income-related inequality and inequity in children’s health care: A longitudinal analysis using data from Brazil," Social Science & Medicine, Elsevier, vol. 224(C), pages 127-137.
    9. Makdissi, Paul & Yazbeck, Myra, 2014. "Measuring socioeconomic health inequalities in presence of multiple categorical information," Journal of Health Economics, Elsevier, vol. 34(C), pages 84-95.
    10. Allanson, Paul, 2010. "Longitudinal analysis of income-related health inequality: welfare foundations and alternative measures," SIRE Discussion Papers 2010-71, Scottish Institute for Research in Economics (SIRE).
    11. Merino Ventosa, María & Urbanos-Garrido, Rosa M.maria.merino.ven@gmail.com, 2016. "Disentangling effects of socioeconomic status on obesity: A cross-sectional study of the Spanish adult population," Economics & Human Biology, Elsevier, vol. 22(C), pages 216-224.
    12. Hai Zhong, 2010. "On decomposing the inequality and inequity change in health care utilization: change in means, or change in the distributions?," International Journal of Health Economics and Management, Springer, vol. 10(4), pages 369-386, December.
    13. I. Josa & A. Aguado, 2020. "Measuring Unidimensional Inequality: Practical Framework for the Choice of an Appropriate Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(2), pages 541-570, June.
    14. Mohammad Habibullah Pulok & Kees Gool & Mohammad Hajizadeh & Sara Allin & Jane Hall, 2020. "Measuring horizontal inequity in healthcare utilisation: a review of methodological developments and debates," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(2), pages 171-180, March.
    15. Peng Nie & Andrew E. Clarck & Conchita D'Ambrosio & Lanlin Ding, 2020. "Income-related health inequality in urban China (1991-2015): The role of homeownership and housing conditions," Working Papers 524, ECINEQ, Society for the Study of Economic Inequality.
    16. 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.
    17. Chen, Zhuo & Roy, Kakoli, 2009. "Calculating concentration index with repetitive values of indicators of economic welfare," Journal of Health Economics, Elsevier, vol. 28(1), pages 169-175, January.
    18. Owen O’Donnell & Eddy van Doorslaer & Adam Wagstaff, 2012. "Decomposition of Inequalities in Health and Health Care," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 17, Edward Elgar Publishing.
    19. Solmi, Francesca & Von Wagner, Christian & Kobayashi, Lindsay C. & Raine, Rosalind & Wardle, Jane & Morris, Stephen, 2015. "Decomposing socio-economic inequality in colorectal cancer screening uptake in England," Social Science & Medicine, Elsevier, vol. 134(C), pages 76-86.
    20. Makdissi, Paul & Yazbeck, Myra, 2016. "Avoiding blindness to health status in health achievement and health inequality measurement," Social Science & Medicine, Elsevier, vol. 171(C), pages 39-47.

    More about this item

    Keywords

    Health Inequality; Non-Continuous data; Copulas; Quantile Regression;
    All these keywords.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:yor:hectdg:09/24. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/deyoruk.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jane Rawlings (email available below). General contact details of provider: https://edirc.repec.org/data/deyoruk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.