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

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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.

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Notes

  1. ‘Two points are said to be antipodal (i.e., each is the antipode of the other) if they are diametrically opposite. Examples include endpoints of a line segment or poles of a sphere.’ (from Wolfram MathWorld).

  2. For a nice survey of income polarization, see Chap. 4 in Chakravarty [6].

  3. The literature actually makes a distinction between a relative [9], an absolute [10], and an intermediate approach to bipolarization [7].

  4. For a recent work on this topic, see, Chakravarty and Maharaj [8].

  5. We thank Conchita D'Ambrosio for reminding us of this useful classification of the different concepts of polarization, which was already suggested by Duclos et al. [15].

  6. The emphasis in such a case is then on the existence of a clustering of incomes around local poles.

  7. The same kind of distinction was in a certain way already suggested by Silber and Yalonetzky [28] who proposed two families of indices measuring inequality in life chances in the case of ordinal variables.

  8. It is evidently assumed that not all the population subgroups are concentrated in the same health category. Otherwise the classification into different health categories would be irrelevant.

  9. Note that in some cases the index POLOR1, which is based on a logarithmic function, could not be computed because some proportions were equal to zero. This was the case for Cyprus (see Table 2) but also for several other countries in some bootstrap samples. We then decided to discard the POLOR1 index from our empirical application.

  10. Naturally there could be other reasons for inter-country variation in social polarization, such as differences in the structure by age.

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Authors and Affiliations

  1. CEPS/INSTEAD, 3 Avenue de la Fonte, 4364, Esch-sur-Alzette, Luxembourg

    Alessio Fusco & Jacques Silber

  2. Department of Economics, Bar-Ilan University, Ramat Gan, Israel

    Jacques Silber

Authors
  1. Alessio Fusco
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  2. Jacques Silber
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Correspondence to Jacques Silber.

Additional information

This paper was started when Jacques Silber was visiting professor at CEPS/INSTEAD which he thanks for its very warm hospitality. He also gratefully acknowledges the financial support of the Adar Foundation of the Department of Economics of Bar-Ilan University. Core funding for CEPS/INSTEAD from the Ministry of Higher Education and Research of Luxembourg is gratefully acknowledged by Alessio Fusco. Both authors thank Gaston Yalonetzky for his very useful comments on a previous draft of this paper.

Appendix

Appendix

See Tables 5 and 6.

Table 5 Number of observations by country
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Table 6 Citizenship of the respondents by country (2009), row percentages add up to 100
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Fusco, A., Silber, J. On social polarization and ordinal variables: the case of self-assessed health. Eur J Health Econ 15, 841–851 (2014). https://doi.org/10.1007/s10198-013-0529-5

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