IDEAS home Printed from https://ideas.repec.org/a/wly/hlthec/v26y2017i7p937-956.html
   My bibliography  Save this article

The Income–Health Relationship ‘Beyond the Mean’: New Evidence from Biomarkers

Author

Listed:
  • Vincenzo Carrieri
  • Andrew M. Jones

Abstract

The relationship between income and health is one of the most explored topics in health economics but less is known about this relationship at different points of the health distribution. Analysis based solely on the mean may miss important information in other parts of the distribution. This is especially relevant when clinical concern is focused on the tail of the distribution and when evaluating the income gradient at different points of the distribution and decomposing income‐related inequalities in health is of interest. We use the unconditional quantile regression approach to analyse the income gradient across the entire distribution of objectively measured blood‐based biomarkers. We apply an Oaxaca–Blinder decomposition at various quantiles of the biomarker distributions to analyse gender differentials in biomarkers and to measure the contribution of income (and other covariates) to these differentials. Using data from the Health Survey for England, we find a non‐linear relationship between income and health and a strong gradient with respect to income at the highest quantiles of the biomarker distributions. We find that there is heterogeneity in the association of health to income across genders, which accounts for a substantial percentage of the gender differentials in observed health. Copyright © 2016 John Wiley & Sons, Ltd.

Suggested Citation

  • Vincenzo Carrieri & Andrew M. Jones, 2017. "The Income–Health Relationship ‘Beyond the Mean’: New Evidence from Biomarkers," Health Economics, John Wiley & Sons, Ltd., vol. 26(7), pages 937-956, July.
  • Handle: RePEc:wly:hlthec:v:26:y:2017:i:7:p:937-956
    DOI: 10.1002/hec.3372
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/hec.3372
    Download Restriction: no

    File URL: https://libkey.io/10.1002/hec.3372?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2006. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," American Economic Review, American Economic Association, vol. 96(4), pages 988-1012, September.
    2. Anna Choi & John Cawley, 2018. "Health disparities across education: The role of differential reporting error," Health Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 1-29, March.
    3. Hendrik Jürges & Eberhard Kruk & Steffen Reinhold, 2013. "The effect of compulsory schooling on health—evidence from biomarkers," Journal of Population Economics, Springer;European Society for Population Economics, vol. 26(2), pages 645-672, April.
    4. Ettner, Susan L., 1996. "New evidence on the relationship between income and health," Journal of Health Economics, Elsevier, vol. 15(1), pages 67-85, February.
    5. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    6. Cristina Hernandez-Quevedo & Andrew M Jones & Nigel Rice, "undated". "Reporting Bias and Heterogeneity in Self-Assessed Health. Evidence from the British Household Panel Survey," Discussion Papers 04/18, Department of Economics, University of York.
    7. Ben Jann, 2008. "The Blinder–Oaxaca decomposition for linear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 453-479, December.
    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. David Cutler & Angus Deaton & Adriana Lleras-Muney, 2006. "The Determinants of Mortality," Journal of Economic Perspectives, American Economic Association, vol. 20(3), pages 97-120, Summer.
    10. Teresa Bago d'Uva & Eddy Van Doorslaer & Maarten Lindeboom & Owen O'Donnell, 2008. "Does reporting heterogeneity bias the measurement of health disparities?," Health Economics, John Wiley & Sons, Ltd., vol. 17(3), pages 351-375, March.
    11. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    12. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    13. Andrew Jones & Ángel López Nicolás, 2006. "Allowing for heterogeneity in the decomposition of measures of inequality in health," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 4(3), pages 347-365, December.
    14. Ploubidis, George B. & Benova, Lenka & Grundy, Emily & Laydon, Daniel & DeStavola, Bianca, 2014. "Lifelong Socio Economic Position and biomarkers of later life health: Testing the contribution of competing hypotheses," Social Science & Medicine, Elsevier, vol. 119(C), pages 258-265.
    15. Heckley, Gawain & Gerdtham, Ulf-G. & Kjellsson, Gustav, 2016. "A general method for decomposing the causes of socioeconomic inequality in health," Journal of Health Economics, Elsevier, vol. 48(C), pages 89-106.
    16. 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.
    17. David Neumark, 1988. "Employers' Discriminatory Behavior and the Estimation of Wage Discrimination," Journal of Human Resources, University of Wisconsin Press, vol. 23(3), pages 279-295.
    18. Jones, A. & Lomas, J. & Rice, N., 2014. "Going Beyond the Mean in Healthcare Cost Regressions: a Comparison of Methods for Estimating the Full Conditional Distribution," Health, Econometrics and Data Group (HEDG) Working Papers 14/26, HEDG, c/o Department of Economics, University of York.
    19. Kakwani, Nanak & Wagstaff, Adam & van Doorslaer, Eddy, 1997. "Socioeconomic inequalities in health: Measurement, computation, and statistical inference," Journal of Econometrics, Elsevier, vol. 77(1), pages 87-103, March.
    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. Davillas, Apostolos & Pudney, Stephen, 2020. "Using biomarkers to predict healthcare costs: Evidence from a UK household panel," Journal of Health Economics, Elsevier, vol. 73(C).
    2. Chris Muris & Pedro Raposo & Sotiris Vandoros, 2020. "A dynamic ordered logit model with fixed effects," Papers 2008.05517, arXiv.org.
    3. Peng Nie & Qing Li & Alan A. Cohen & Alfonso Sousa-Poza, 2021. "In search of China’s income-health gradient: a biomarker-based analysis," Applied Economics, Taylor & Francis Journals, vol. 53(48), pages 5599-5618, October.
    4. Gabriella Berloffa & Francesca Paolini, 2019. "Decomposing Immigrant Differences in Physical and Mental Health: A 'Beyond the Mean' Analysis," DEM Working Papers 2019/4, Department of Economics and Management.
    5. Davillas, Apostolos & Pudney, Stephen, 2020. "Biomarkers, disability and health care demand," Economics & Human Biology, Elsevier, vol. 39(C).
    6. Davillas, Apostolos & Pudney, Stephen, 2019. "Baseline health and public healthcare costs five years on: a predictive analysis using biomarker data in a prospective household panel," ISER Working Paper Series 2019-01, Institute for Social and Economic Research.
    7. Atkins, Rose & Turner, Alex James & Chandola, Tarani & Sutton, Matt, 2020. "Going beyond the mean in examining relationships of adolescent non-cognitive skills with health-related quality of life and biomarkers in later-life," Economics & Human Biology, Elsevier, vol. 39(C).
    8. Alexander Silbersdorff & Julia Lynch & Stephan Klasen & Thomas Kneib, 2018. "Reconsidering the income‐health relationship using distributional regression," Health Economics, John Wiley & Sons, Ltd., vol. 27(7), pages 1074-1088, July.
    9. Davillas, Apostolos & Jones, Andrew M, 2020. "Ex ante inequality of opportunity in health, decomposition and distributional analysis of biomarkers," Journal of Health Economics, Elsevier, vol. 69(C).
    10. Apostolos Davillas & Andrew M. Jones, 2018. "Parametric models for biomarkers based on flexible size distributions," Health Economics, John Wiley & Sons, Ltd., vol. 27(10), pages 1617-1624, October.
    11. Davillas, Apostolos & Pudney, Stephen, 2020. "Biomarkers as precursors of disability," Economics & Human Biology, Elsevier, vol. 36(C).
    12. Swaminathan, Harini & Sharma, Anurag & Shah, Narendra G., 2019. "Does the relationship between income and child health differ across income groups? Evidence from India," Economic Modelling, Elsevier, vol. 79(C), pages 57-73.
    13. Andrew M. Jones, 2019. "Equity, opportunity and health," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(3), pages 413-421, August.
    14. Nesson, Erik T. & Robinson, Joshua J., 2019. "On the measurement of health and its effect on the measurement of health inequality," Economics & Human Biology, Elsevier, vol. 35(C), pages 207-221.

    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. Carrieri, V. & Jones, A.M., 2015. "The Income-Health Relationship “Beyond the Mean†: New Evidence from Biomarkers," Health, Econometrics and Data Group (HEDG) Working Papers 15/22, HEDG, c/o Department of Economics, University of York.
    2. 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.
    3. Huong Thu Le & Ha Trong Nguyen, 2018. "The evolution of the gender test score gap through seventh grade: new insights from Australia using unconditional quantile regression and decomposition," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 7(1), pages 1-42, December.
    4. Sonja C. Kassenboehmer & Mathias G. Sinning, 2014. "Distributional Changes in the Gender Wage Gap," ILR Review, Cornell University, ILR School, vol. 67(2), pages 335-361, April.
    5. Gabriella Berloffa & Francesca Paolini, 2019. "Decomposing Immigrant Differences in Physical and Mental Health: A 'Beyond the Mean' Analysis," DEM Working Papers 2019/4, Department of Economics and Management.
    6. Kajal Lahiri & Zulkarnain Pulungan, 2006. "Health Inequality and Its Determinants in New York," Discussion Papers 06-03, University at Albany, SUNY, Department of Economics.
    7. Kilic, Talip & Palacios-López, Amparo & Goldstein, Markus, 2015. "Caught in a Productivity Trap: A Distributional Perspective on Gender Differences in Malawian Agriculture," World Development, Elsevier, vol. 70(C), pages 416-463.
    8. Antonio Di Paolo & Joan Gil Trasfi & Athina Raftopoulou, 2018. "“What drives regional differences in BMI? Evidence from Spain”," IREA Working Papers 201808, University of Barcelona, Research Institute of Applied Economics, revised Oct 2018.
    9. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    10. Nguyen, Ha, 2015. "The evolution of the gender test score gap through seventh grade: New insights from Australia using quantile regression and decomposition," MPRA Paper 67586, University Library of Munich, Germany.
    11. Sonja C. Kassenböhmer & Mathias Sinning, 2010. "Distributional Changes in the Gender Wage Gap," Ruhr Economic Papers 0220, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    12. Rama Lionel Ngenzebuke, 2017. "The Returns of "I Do": Multifaceted Female Decision-making and Agricultural Yields in Tanzania," Working Papers ECARES ECARES 2017-05, ULB -- Universite Libre de Bruxelles.
    13. 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.
    14. Gomes, Magno Rogério & Souza, Solange de Cássia Inforzato de & Mantovani, Gabriela Gomes & Paiva, Vanessa Fortunato de, 2020. "Wage gap decomposition models: A methodological contribution," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 39(2), March.
    15. Asif, Atta Muhammad & Akbar, Muhammad, 2021. "On the decomposition of rank-dependent indicator of socio-economic inequalities in child malnutrition: Some empirical findings," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    16. Andrej Cupák & Pavel Ciaian & d'Artis Kancs, 2021. "Comparing the immigrant-native pay gap: A novel evidence from home and host countries," EERI Research Paper Series EERI RP 2021/05, Economics and Econometrics Research Institute (EERI), Brussels.
    17. repec:zbw:rwirep:0220 is not listed on IDEAS
    18. David Cantarero & Marta Pascual & Jose Maria Sarabia, 2004. "Can income inequality contribute to understand inequalities in health? An empirical approach based on the European Community Household Panel," ERSA conference papers ersa04p230, European Regional Science Association.
    19. Gomes, Magno Rogério & Souza, Solange de Cássia Inforzato de & Mantovani, Gabriela Gomes & Paiva, Vanessa Fortunato de, 2019. "Wage gap decomposition models: A methodological contribution," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 39(2).
    20. Nesson, Erik T. & Robinson, Joshua J., 2019. "On the measurement of health and its effect on the measurement of health inequality," Economics & Human Biology, Elsevier, vol. 35(C), pages 207-221.
    21. Brahim Boudarbat & Marie Connolly, 2013. "The gender wage gap among recent post‐secondary graduates in Canada: a distributional approach," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 46(3), pages 1037-1065, August.

    More about this item

    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:wly:hlthec:v:26:y:2017:i:7:p:937-956. See general information about how to correct material in RePEc.

    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: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/5749 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.