IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp13692.html
   My bibliography  Save this paper

The Relationship between Subjective Wellbeing and Subjective Wellbeing Inequality: Taking Ordinality and Skewness Seriously

Author

Listed:
  • Grimes, Arthur

    (Motu Economic and Public Policy Research Trust)

  • Jenkins, Stephen P.

    (London School of Economics)

  • Tranquilli, Florencia

    (Motu Economic and Public Policy Research Trust)

Abstract

We argue that the relationship between individual satisfaction with life (SWL) and SWL inequality is more complex than described by leading earlier research such as Goff, Helliwell, and Mayraz (Economic Inquiry, 2018). Using inequality indices appropriate for ordinal data, our analysis using the World Values Survey reveals that skewness of the SWL distribution, not only inequality, matters for individual SWL outcomes; so too does whether we look upwards or downwards at the (skewed) distribution. Our results are consistent with there being negative (positive) externalities for an individual's SWL from seeing people who are low (high) in the SWL distribution.

Suggested Citation

  • Grimes, Arthur & Jenkins, Stephen P. & Tranquilli, Florencia, 2020. "The Relationship between Subjective Wellbeing and Subjective Wellbeing Inequality: Taking Ordinality and Skewness Seriously," IZA Discussion Papers 13692, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp13692
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp13692.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Stephen P. Jenkins, 2020. "Better off? Distributional comparisons for ordinal data about personal well-being," New Zealand Economic Papers, Taylor & Francis Journals, vol. 54(3), pages 211-238, September.
    2. David M Kaplan & Wei Zhao, 2023. "Comparing latent inequality with ordinal data," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 189-214.
    3. 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.
    4. Benedicte Apouey, 2007. "Measuring health polarization with self‐assessed health data," Health Economics, John Wiley & Sons, Ltd., vol. 16(9), pages 875-894, September.
    5. Ravallion, Martin & Lokshin, Michael, 2000. "Who wants to redistribute?: The tunnel effect in 1990s Russia," Journal of Public Economics, Elsevier, vol. 76(1), pages 87-104, April.
    6. Betsey Stevenson & Justin Wolfers, 2008. "Happiness Inequality in the United States," The Journal of Legal Studies, University of Chicago Press, vol. 37(S2), pages 33-79, June.
    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. Pascarn R. Dickinson & Philip S. Morrison, 2022. "Aversion to Local Wellbeing Inequality is Moderated by Social Engagement and Sense of Community," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(3), pages 907-926, February.

    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. Arthur Grimes & Stephen P. Jenkins & Florencia Tranquilli, 2023. "The Relationship Between Subjective Wellbeing and Subjective Wellbeing Inequality: An Important Role for Skewness," Journal of Happiness Studies, Springer, vol. 24(1), pages 309-330, January.
    2. Stephen P. Jenkins, 2020. "Comparing distributions of ordinal data," Stata Journal, StataCorp LP, vol. 20(3), pages 505-531, September.
    3. Stephen P. Jenkins, 2021. "Inequality Comparisons with Ordinal Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(3), pages 547-563, September.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Bénédicte Apouey & David Madden, 2023. "Health poverty," Chapters, in: Jacques Silber (ed.), Research Handbook on Measuring Poverty and Deprivation, chapter 19, pages 202-211, Edward Elgar Publishing.
    12. 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.
    13. 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.
    14. 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.
    15. Indranil Dutta & James Foster, 2011. "Inequality of Happiness in US: 1972-2008," Economics Discussion Paper Series 1110, Economics, The University of Manchester.
    16. 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.
    17. Indranil Dutta & James Foster, 2013. "Inequality of Happiness in the U.S.: 1972–2010," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 59(3), pages 393-415, September.
    18. 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.
    19. 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.
    20. repec:hal:pseose:halshs-00850014 is not listed on IDEAS
    21. 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.

    More about this item

    Keywords

    skewness; subjective wellbeing; ordinal data; inequality; WVS;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

    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:iza:izadps:dp13692. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    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.