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

Anjan Ray Chaudhury and Madhabendra Sinha

Journal of Policy Modeling, 2019, vol. 41, issue 6, 1095-1108

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.

Keywords: Multi-group segregation; Nominal categorical data; Ordinal categorical data; Scheduled castes; Scheduled tribes (search for similar items in EconPapers)
JEL-codes: I30 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jpolmo:v:41:y:2019:i:6:p:1095-1108

DOI: 10.1016/j.jpolmod.2019.04.002

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