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Multi-group segregation for nominal and ordinal categorical data: An application to socio-religious groups in India

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  • Ray Chaudhury, Anjan
  • Sinha, Madhabendra

Abstract

This study is an attempt to construct some summary measures of multi-group segregation for nominal and ordinal categorical data. These measures are developed by taking into account the association between identity groups and unordered or ordered categories of the well-being indicator and also the disproportionate representation of the populations of the identity groups across the unordered or ordered categories of the well-being indicator. The newly developed measures are characterized and applied to assess the disparities in education and occupational status among the socio-religious groups in India. Empirical findings reveal the existence of between-group inequality in education and occupation in India, and some relevant policies to reduce these inequalities are also suggested.

Suggested Citation

  • Ray Chaudhury, Anjan & Sinha, Madhabendra, 2019. "Multi-group segregation for nominal and ordinal categorical data: An application to socio-religious groups in India," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1095-1108.
    • Handle: RePEc:eee:jpolmo:v:41:y:2019:i:6:p:1095-1108
    DOI: 10.1016/j.jpolmod.2019.04.002
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    References listed on IDEAS

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    More about this item

    Keywords

    Multi-group segregation; Nominal categorical data; Ordinal categorical data; Scheduled castes; Scheduled tribes;
    All these keywords.

    JEL classification:

    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General

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