IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v130y2015icp109-112.html
   My bibliography  Save this article

Estimation of inequality indices of the cumulative distribution function

Author

Listed:
  • Abul Naga, Ramses H.
  • Stapenhurst, Christopher

Abstract

Inequality indices for self-assessed health and life satisfaction are typically constructed as functions of the cumulative distribution function. We present a unified methodology for the estimation of the resulting inequality indices. We also obtain explicit standard error formulas in the context of two popular families of inequality indices that have emerged from this literature.

Suggested Citation

  • Abul Naga, Ramses H. & Stapenhurst, Christopher, 2015. "Estimation of inequality indices of the cumulative distribution function," Economics Letters, Elsevier, vol. 130(C), pages 109-112.
    • Handle: RePEc:eee:ecolet:v:130:y:2015:i:c:p:109-112
    DOI: 10.1016/j.econlet.2015.03.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016517651500097X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2015.03.004?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Benedicte Apouey, 2007. "Measuring health polarization with self‐assessed health data," Health Economics, John Wiley & Sons, Ltd., vol. 16(9), pages 875-894, September.
    2. 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.
    3. 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.
    4. Anderson, Gordon, 1996. "Nonparametric Tests of Stochastic Dominance in Income Distributions," Econometrica, Econometric Society, vol. 64(5), pages 1183-1193, September.
    5. Yves Arrighi & Mohammad Abu‐Zaineh & Bruno Ventelou, 2015. "To Count or Not to Count Deaths: Reranking Effects in Health Distribution Evaluation," Health Economics, John Wiley & Sons, Ltd., vol. 24(2), pages 193-205, February.
    6. Kobus, Martyna & Miłoś, Piotr, 2012. "Inequality decomposition by population subgroups for ordinal data," Journal of Health Economics, Elsevier, vol. 31(1), pages 15-21.
    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.
    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. 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.
    2. 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.
    3. Ramses H. Abul Naga & Christopher Stapenhurst & Gaston Yalonetzky, 2024. "Inferring inequality: Testing for median-preserving spreads in ordinal data," Econometric Reviews, Taylor & Francis Journals, vol. 43(2-4), pages 156-174, April.
    4. Frank A Cowell & Martyna Kobus & Radoslaw Kurek, 2017. "Welfare and Inequality Comparisons for Uni- and Multi-dimensional Distributions of Ordinal Data," STICERD - Public Economics Programme Discussion Papers 31, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    5. Roman Matkovskyy, 2020. "A measurement of affluence and poverty interdependence across countries: Evidence from the application of tail copula," Bulletin of Economic Research, Wiley Blackwell, vol. 72(4), pages 404-416, October.
    6. Sandip Sarkar & Sattwik Santra, 2020. "Extending the approaches to polarization ordering of ordinal variables," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(3), pages 421-440, September.
    7. 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.
    8. 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.
    9. Debasmita Basu & Sandip Sarkar, 2023. "Polarization in Indian Education: An Ordinal Variable Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(3), pages 569-591, September.

    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. 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.
    2. Mohammad Abu-Zaineh & Ramses H. Abul Naga, 2019. "Bread and Social Justice: Measurement of Social Welfare and Inequalities Using Anthropometrics," AMSE Working Papers 1930, Aix-Marseille School of Economics, France.
    3. 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.
    4. 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.
    5. Bénédicte Apouey & Jacques Silber, 2013. "Inequality and Bi-Polarization in Socioeconomic Status and Health: Ordinal Approaches," Research on Economic Inequality, in: Health and Inequality, volume 21, pages 77-109, Emerald Group Publishing Limited.
    6. Fatiha Bennia & Nicolas Gravel & Brice Magdalou & Patrick Moyes, 2022. "Is body weight better distributed among men than among women? A robust normative analysis for France, the UK, and the US," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(1), pages 69-103, January.
    7. Di Novi, C. & Piacenza, M. & Robone, S. & Turati, G., 2015. "How does fiscal decentralization affect within-regional disparities in well-being? Evidence from health inequalities in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 15/23, HEDG, c/o Department of Economics, University of York.
    8. Yalonetzky, Gaston, 2022. "Consistent and inconsistent inequality indices for ordinal variables," Economics Letters, Elsevier, vol. 219(C).
    9. Nicolas Gravel & Brice Magdalou & Patrick Moyes, 2021. "Ranking distributions of an ordinal variable," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 71(1), pages 33-80, February.
    10. Suman Seth and Gaston Yalonetzky, 2018. "Assessing Deprivation with Ordinal Variables: Depth Sensitivity and Poverty Aversion," OPHI Working Papers ophiwp123.pdf, Queen Elizabeth House, University of Oxford.
    11. Tugce Cuhadaroglu, 2023. "Evaluating ordinal inequalities between groups," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 21(1), pages 219-231, March.
    12. Martyna Kobus, 2014. "Multidimensional polarization for ordinal data," Working Papers 326, ECINEQ, Society for the Study of Economic Inequality.
    13. Sandip Sarkar & Sattwik Santra, 2020. "Extending the approaches to polarization ordering of ordinal variables," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(3), pages 421-440, September.
    14. repec:hal:pseose:halshs-00850014 is not listed on IDEAS
    15. Debasmita Basu & Sandip Sarkar, 2023. "Polarization in Indian Education: An Ordinal Variable Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(3), pages 569-591, September.
    16. Marta Pascual & David Cantarero & Paloma Lanza, 2018. "Health polarization and inequalities across Europe: an empirical approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(8), pages 1039-1051, November.
    17. Martyna Kobus, 2014. "On the measurement of polarization for ordinal data," Working Papers 325, ECINEQ, Society for the Study of Economic Inequality.
    18. 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.
    19. 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.
    20. Kobus, Martyna & Kurek, Radosław, 2023. "Measuring inequality in the joint distribution of socioeconomic status and health," Economics Letters, Elsevier, vol. 226(C).
    21. Christoffer Sonne-Schmidt & Finn Tarp & Lars Peter Østerdal, 2016. "Ordinal Bivariate Inequality: Concepts and Application to Child Deprivation in Mozambique," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(3), pages 559-573, September.

    More about this item

    Keywords

    Ordered response data; Self-assessed health; Multinomial sampling; Large sample distributions; Standard errors;
    All these keywords.

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • I1 - Health, Education, and Welfare - - Health

    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:130:y:2015:i:c:p:109-112. 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.