IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v162y2018icp76-80.html

Bayesian inference for health inequality and welfare using qualitative data

Author

Listed:
  • Gunawan, David
  • Griffiths, William E.
  • Chotikapanich, Duangkamon

Abstract

We show how to use Bayesian inference to compare two ordinal categorical distributions commonly occurring with data on self-reported health status. Procedures for computing probabilities for first and second order stochastic dominance and S-dominance are described, along with methodology for obtaining posterior densities for health inequality indexes. The techniques are applied to four years of data on Australian self-reported health status.

Suggested Citation

  • Gunawan, David & Griffiths, William E. & Chotikapanich, Duangkamon, 2018. "Bayesian inference for health inequality and welfare using qualitative data," Economics Letters, Elsevier, vol. 162(C), pages 76-80.
    • Handle: RePEc:eee:ecolet:v:162:y:2018:i:c:p:76-80
    DOI: 10.1016/j.econlet.2017.11.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176517304603
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2017.11.005?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
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Abul Naga, Ramses H. & Yalcin, Tarik, 2008. "Inequality measurement for ordered response health data," Journal of Health Economics, Elsevier, vol. 27(6), pages 1614-1625, December.
    2. Gaston Yalonetzky, 2013. "Stochastic Dominance with Ordinal Variables: Conditions and a Test," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 126-163, January.
    3. David Madden, 2010. "Ordinal and cardinal measures of health inequality: an empirical comparison," Health Economics, John Wiley & Sons, Ltd., vol. 19(2), pages 243-250, February.
    4. Frank A. Cowell & Emmanuel Flachaire, 2017. "Inequality with Ordinal Data," Economica, London School of Economics and Political Science, vol. 84(334), pages 290-321, April.
    5. 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.
    6. Duangkamon Chotikapanich & William E. Griffiths, 2006. "Bayesian Assessment of Lorenz and Stochastic Dominance in Income Distributions," Department of Economics - Working Papers Series 960, The University of Melbourne.
    7. 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.
    8. Joan Costa Font & Frank Cowell, 2013. "Measuring Health Inequality with Categorical Data: Some Regional Patterns," Research on Economic Inequality, in: Health and Inequality, volume 21, pages 53-76, Emerald Group Publishing Limited.
    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. David M Kaplan & Wei Zhao, 2023. "Comparing latent inequality with ordinal data," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 189-214.

    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. Valérie Bérenger & Jacques Silber, 2022. "On the Measurement of Happiness and of its Inequality," Journal of Happiness Studies, Springer, vol. 23(3), pages 861-902, March.
    2. David Gunawan & William Griffths & Duangkamon Chotikapanich, 2017. "Bayesian Inference for Health Inequality and Welfare Using Qualitative Data "Abstract: We show how to use Bayesian inference to compare two ordinal categorical distributions commonly occurring with data on self-reported health status. Procedures," Department of Economics - Working Papers Series 2031, The University of Melbourne.
    3. Joan Costa-Font & Frank A. Cowell, 2022. "The measurement of health inequalities: does status matter?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(2), pages 299-325, June.
    4. 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.
    5. Maria Livia ŞTEFĂNESCU, 2015. "Analyzing the health status of the population using ordinal data," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 3(1), pages 18-24, June.
    6. David M Kaplan & Wei Zhao, 2023. "Comparing latent inequality with ordinal data," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 189-214.
    7. David Madden, 2011. "The Impact of an Economic Boom on the Level and Distribution of Subjective Well-Being: Ireland, 1994–2001," Journal of Happiness Studies, Springer, vol. 12(4), pages 667-679, August.
    8. SILBER, Jacques & XU, Yongsheng, 2016. "The Health Equivalent Adjusted Level (HEAL): Taking an Ordinal Approach to the Measurement of a Society's Health Achievements," Discussion paper series HIAS-E-31, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    9. Martyna Kobus & Olga Półchłopek & Gaston Yalonetzky, 2019. "Inequality and Welfare in Quality of Life Among OECD Countries: Non-parametric Treatment of Ordinal Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 201-232, May.
    10. Vanesa Jorda & Borja López-Noval & José María Sarabia, 2019. "Distributional Dynamics of Life Satisfaction in Europe," Journal of Happiness Studies, Springer, vol. 20(4), pages 1015-1039, April.
    11. Ramses Abul Naga & Christopher Stapenhurst & Gaston Yalonetzky, 2020. "Asymptotic Versus Bootstrap Inference for Inequality Indices of the Cumulative Distribution Function," Econometrics, MDPI, vol. 8(1), pages 1-15, February.
    12. Bénédicte Apouey & Jacques Silber & Yongsheng Xu, 2020. "On Inequality‐Sensitive and Additive Achievement Measures Based on Ordinal Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(2), pages 267-286, June.
    13. Adi Lazar & Jacques Silber, 2013. "On The Cardinal Measurement Of Health Inequality When Only Ordinal Information Is Available On Individual Health Status," Health Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 106-113, January.
    14. Martyna Kobus & Radosław Kurek, 2019. "Multidimensional polarization for ordinal data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(3), pages 301-317, September.
    15. Stephen P. Jenkins, 2020. "Comparing distributions of ordinal data," Stata Journal, StataCorp LLC, vol. 20(3), pages 505-531, September.
    16. Chrysanthi Hatzimasoura & Christopher J. Bennett, 2011. "Poverty Measurement with Ordinal Data," Working Papers 2011-14, The George Washington University, Institute for International Economic Policy.
    17. Jones, Andrew M. & Rice, Nigel & Robone, Silvana & Dias, Pedro Rosa, 2011. "Inequality and polarisation in health systems' responsiveness: A cross-country analysis," Journal of Health Economics, Elsevier, vol. 30(4), pages 616-625, July.
    18. Simeone Enza, 2025. "Inequality in Health Status During the COVID-19 in the UK: Does the Impact of the Second Lockdown Policy Matter?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 25(3), pages 449-503.
    19. Hongliang Wang & Yiwen Yu, 2016. "Increasing health inequality in China: An empirical study with ordinal data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 14(1), pages 41-61, March.
    20. 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.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

    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:eee:ecolet:v:162:y:2018:i:c:p:76-80. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.