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Comparing distributions of ordinal data

Author

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  • Stephen P. Jenkins

    (London School of Economics and Political Science)

Abstract

To compare distributions of ordinal data such as individuals’ responses on Likert-type scale variables summarizing subjective well-being, we should not apply the toolbox of methods developed for cardinal variables such as income. Instead, we should use an analogous toolbox that accounts for the ordinal nature of the responses. In this article, I review these methods and introduce a new command, ineqord, for undertaking distributional comparisons. As the empirical illustrations demonstrate, ineqord can be used for dominance checks as well as for estimation of indices of polarization and inequality.

Suggested Citation

  • Stephen P. Jenkins, 2020. "Comparing distributions of ordinal data," Stata Journal, StataCorp LLC, vol. 20(3), pages 505-531, September.
    • Handle: RePEc:tsj:stataj:v:20:y:2020:i:3:p:505-531
    DOI: 10.1177/1536867X20953565
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    Cited by:

    1. 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.
    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. Olivier Bargain & Maria Lo Bue & Francesco Palmisano, 2022. "Dynastic Measures of Intergenerational Mobility," Working Papers hal-03896551, HAL.
    4. Alexandri, Eva & Antón, José-Ignacio & Lewney, Richard, 2024. "The impact of climate change mitigation policies on European labour markets," Ecological Economics, Elsevier, vol. 216(C).
    5. Fakih, Ali & Makdissi, Paul & Marrouch, Walid & Tabri, Rami V. & Yazbeck, Myra, 2022. "A stochastic dominance test under survey nonresponse with an application to comparing trust levels in Lebanese public institutions," Journal of Econometrics, Elsevier, vol. 228(2), pages 342-358.
    6. Arthur Grimes, 2022. "Measuring Pandemic and Lockdown Impacts on Wellbeing," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(2), pages 409-427, June.
    7. Flaviana Palmisano, 2026. "Exploring Population Heterogeneities in Health Dynamics," Health Economics, John Wiley & Sons, Ltd., vol. 35(5), pages 691-711, May.
    8. Jan Delhey & Stephanie Hess & Klaus Boehnke & Franziska Deutsch & Jan Eichhorn & Ulrich Kühnen & Christian Welzel, 2023. "Life Satisfaction During the COVID-19 Pandemic: The Role of Human, Economic, Social, and Psychological Capital," Journal of Happiness Studies, Springer, vol. 24(7), pages 2201-2222, October.
    9. 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.
    10. Jan Delhey & Marcus Gercke, 2025. "Europeans’ Happiness from an Egalitarian Perspective: More Equal Overall, but Often More Polarized Between Rich and Poor," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 179(1), pages 441-462, August.
    11. Olivier Bargain & Maria C. Lo Bue & Flaviana Palmisano, 2021. "Dynastic measures of inter-generational mobility with empirical evidence from Indonesia," WIDER Working Paper Series wp-2021-70, World Institute for Development Economic Research (UNU-WIDER).

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    Keywords

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    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

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