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Occupational Segregation in the Indian Labour Market

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Abstract

This article measures the extent of occupational segregation for gender and social groups in India. It is based on a recent round of a nationally representative employment and unemployment survey of the Government of India. We use overall and local measures of occupational segregation. We find that occupational segregation for both genders and social groups is higher in the urban sector than in the rural sector. Females are more segregated than their male counterparts in both sectors. Among social groups, scheduled caste and scheduled tribe groups have higher levels of segregation. Furthermore, we find that regular workers and the elderly are more segregated when we examine segregation, respectively, by nature of employment and across age groups.

Abstract

Cet article mesure l’étendue de la ségrégation occupationnelle en fonction du genre et du groupe social en Inde. Cet article s’appuie sur un sondage représentatif à l’échelle nationale sur l’emploi et le chômage, récemment réalisé par le Gouvernement Indien. Nous utilisons des mesure générales et locales pour la ségrégation occupationnelle. Nous trouvons que la ségrégation occupationnelle pour les deux genres ainsi que pour les divers groupes sociaux est plus importante dans le secteur urbain que dans le secteur rural. Dans les deux secteurs,les femmes sont plus susceptibles de subir la ségrégation que leurs homologues masculins. Parmi les groupes sociaux, les castes et les tribus les plus basses sont les plus affectées par la ségrégation. De plus, nous trouvons que les ouvriers routiniers et les personnes âgées sont plus ségréguées lorsque l’on examine la ségrégation selon la nature de l’emploi ou selon différentes catégories d’âge, respectivement.

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Notes

  1. See Deshpande (2011) for a comprehensive review of caste and discrimination in India.

  2. There is a growing literature on measurement of segregation. Some studies also take into account the prestige or status of occupations (for example, white collar or blue collar occupations). A recent paper by Gradin (2012) examines conditional segregation in the United States.

  3. See Alonso-Villar et al (2012) and Del Río and Alonso-Villar (2010) for an application of these measures.

  4. Employment and unemployment status of individuals can be determined using three different approaches, used in the classification of the activity statuses of the person surveyed. These are usual principal status (UPS), current weekly status and current daily status. UPS indicates the status of a person for a relatively longer period during the reference period of 365 days preceding the date of survey.

  5. The Appendix provides a list of two-digit occupations as per the NCO-04 classification scheme.

  6. This group has a very low proportion of the workforce.

  7. The notations and indices in this paper are based on Alonso-Villar and Del Río (2010).

  8. The ranking of occupational distributions achieved through segregation curves does not depend upon which group is on the horizontal axis and which is on the vertical axis. Like Lorenz curves, segregation curves give a partial or incomplete ranking of distributions (Hutchens, 1991).

  9. These curves are also referred to as employment Lorenz curves. See Alonso-Villar (2011) for a description of employment Lorenz curves and their decompositions.

  10. The dissimilarity index proposed by Duncan and Duncan (1955) is given as: D=(1/2)∑ j |(F j /F)−(M j /M)|.

  11. Index Dg is not consistent with the segregation curve criterion.

  12. The index proposed by Karmel and MacLachlan (1988) is as follows: I P =((1)/(T))∑ j |(1−a)M j −aF j |, where F j and M j are the number of females and males, respectively, in occupation j, a denotes the proportion of males in the overall workforce, and T denotes the total number of individuals in the workforce.

  13. The contribution to overall segregation using the three measures can be expressed as (Cg)/(T)(GEg)/(M), (Cg)/(T)(Gg)/(G) and (Cg)/(T)(Dg)/(I P ), respectively.

  14. We used the ‘localseg’ Stata module to compute segregation indices (available at http://fmwww.bc.edu/repec/bocode/l/localseg.ado).

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Acknowledgements

The author would like to thank Sripad Motiram, S Chandrasekhar, Sudha Narayanan and Ankush Agrawal for comments and suggestions.The author is grateful to two anonymous reviewers of this journal for providing insightful comments. Institutional support provided by Indira Gandhi Institute of Development Research, India is gratefully acknowledged.

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  1. Indira Gandhi Institute of Development Research, Mumbai, India

    Tushar Agrawal

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Appendix

Appendix

List of Occupations

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Agrawal, T. Occupational Segregation in the Indian Labour Market. Eur J Dev Res 28, 330–351 (2016). https://doi.org/10.1057/ejdr.2015.10

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