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On social polarization and ordinal variables: the case of self-assessed health

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  • Alessio Fusco
  • Jacques Silber

Abstract

Social polarization refers to the measurement of the distance between different social groups, defined on the basis of variables such as race, religion, or ethnicity. We propose two approaches to measuring social polarization in the case where the distance between groups is based on an ordinal variable, such as self-assessed health status. The first one, the ‘stratification approach’, amounts to assessing the degree of non-overlapping of the distributions of the ordinal variable between the different population subgroups that are distinguished. The second one, the ‘antipodal approach’, considers that the social polarization of an ordinal variable will be maximal if the individuals belonging to a given population subgroup are in the same health category, this category corresponding either to the lowest or to the highest health status. An empirical illustration is provided using the 2009 cross-sectional data of the European Union Statistics on Income and Living Conditions (EU-SILC). We find that Estonia, Latvia, and Ireland have the highest degree of social polarization when the ordinal variable under scrutiny refers to self-assessed health status and the (unordered) population subgroups to the citizenship of the respondent whereas Luxembourg is the country with the lowest degree of social polarization in health. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Alessio Fusco & Jacques Silber, 2014. "On social polarization and ordinal variables: the case of self-assessed health," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(8), pages 841-851, November.
  • Handle: RePEc:spr:eujhec:v:15:y:2014:i:8:p:841-851
    DOI: 10.1007/s10198-013-0529-5
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    Cited by:

    1. 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.
    2. Mussini Mauro, 2018. "On Measuring Polarization For Ordinal Data: An Approach Based On The Decomposition Of The Leti Index," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 277-296, June.
    3. Tanzhe Tang & Amineh Ghorbani & Flaminio Squazzoni & Caspar G. Chorus, 2022. "Together alone: a group-based polarization measurement," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3587-3619, October.
    4. Francesco Andreoli & Claudio Zoli, 2014. "Measuring Dissimilarity," Working Papers 23/2014, University of Verona, Department of Economics.
    5. Pascual-Sáez, Marta & Cantarero-Prieto, David & Lanza-León, Paloma, 2019. "The dynamics of health poverty in Spain during the economic crisis (2008–2016)," Health Policy, Elsevier, vol. 123(10), pages 1011-1018.
    6. Mauro Mussini, 2018. "On Measuring Polarization For Ordinal Data: An Approach Based On The Decomposition Of The Leti Index," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 277-296, June.
    7. Michail Dolomatov & Vitaly Martynov & Nadezhda Zhuravleva & Elena Zakieva, 2017. "New Indicators of the Level of Social Dissatisfaction in the Planning of Social-Economic Development of the Region," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(1), pages 70-79.

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    More about this item

    Keywords

    EU-SILC; Migration; Ordinal information; Self-assessed health; Social polarization; D63; I14;
    All these keywords.

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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