Abstract
In this chapter, Borooah discusses an important concern of public policy in India which is to ensure that all persons, regardless of gender, caste, or religion, are treated fairly in the jobs market. A key aspect of this relates to inter-group differences in the likelihood of attaining different levels of occupational success. The issue here is whether these differences in likelihood are justified by differences in the distribution of employee attributes or whether they are, wholly or in part, due to employer bias. This chapter attempts to answer these questions using unit record data from the Indian Human Development Survey relating to the period 2011–12. Of particular interest to this chapter is that the Survey provides details about the occupations of approximately 62,500 persons by placing them in one or more of 99 occupations; these are aggregated in the chapter into six broad occupational categories. Using these data, the chapter (focusing on men and women between the ages of 21 and 60) employs the methods of multinomial logit to estimate the probabilities of persons being in these occupational categories, after controlling for their gender/caste/religion and their employment-related attributes. The main focus is the issue of differences between men and women, and differences between persons belonging to different social groups, in their likelihood of being in the different employment categories. Data on these men and women were used to decompose the observed difference between the groups, in their average proportions in the different occupations, into an “employer bias” and an “employee attributes” effect.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
For the history and evolution of caste-based preferential policies in India, see Osborne (2001).
- 2.
For example, converts to Islam from Hindu “unclean occupations”: halalkhors, helas, lalbegis, dhobis, hajjams, chiks, and faqirs. However, extensions were made to the reservations list for Mazhabi Sikhs (in 1956) and neo-Buddhists (in 1990).
- 3.
In arriving at a judgement about who should be eligible for reservation, the criterion has been a person’s caste rather than his/her income or wealth. Consequently, groups belonging to what Article 115 of the Indian Constitution calls “socially and educationally backward classes” have benefited from reservation even though, in practice, many persons belonging to these classes could not be regarded as “socially and educationally backward”; at the same time, many persons belonging to non-backward classes could legitimately be regarded as “socially and educationally backward”. Compounding this anomaly, many of the benefits of reservation have been captured by well-off groups from the depressed classes (e.g. chamars) while poorer groups (e.g. bhangis) have failed to benefit. Unfortunately, it is not possible to address this issue in this study, since the data do not allow a breakdown of the SC by subcaste.
- 4.
Article 340 of the Indian Constitution empowers the government to create such classes, and in 1955, following the report of the Kalelkar Commission, 2339 groups were designated as belonging to the OBC. The 1980 report of the Mandal Commission recommended that, in addition to the 23% of government jobs reserved for the SC and ST, a further 27% be reserved for the OBC. In 1990, V.P. Singh’s government announced plans to implement this recommendation, triggering a wave of “anti-Mandal” rioting in India. In 1992, in Sawhney v. The Union of India, India’s Supreme Court upheld job reservation for the OBC but ruled that (i) reservation was not to extend to more than 50% of the population and (ii) that groups within the OBC category who were manifestly not disadvantaged (the “creamy layer”) were to be excluded from reservation.
- 5.
- 6.
Desai et al. (2015).
- 7.
Of the persons in this category, 95% were agricultural labourers with the remainder engaged in “other farm” activities.
- 8.
Around 94% of persons in the FC category were Hindu, 4% were Christian, and 2% were Sikh.
- 9.
- 10.
Stata’s margin command performs these calculations.
- 11.
The equations were estimated using the svy command in Stata or, in other words, by grossing up the sample observations using weights in IHDS-2011 contained in its FWT variable.
- 12.
The Economist, “A Job of Her Own: Culture and the Labour Market Keep India’s Women at Home”, Briefing: Indian Women, 5 July 2018, https://www.economist.com/briefing/2018/07/05/culture-and-the-labour-market-keep-indias-women-at-home
- 13.
The Economist, op. cit.
- 14.
See the previous chapter for a more detailed discussion.
- 15.
B = 10.2 – 12.9 = −2.7 and C = 8.7 – 9.8 = −1.1, so that B – C = −2.7 + 1.1 = −1.6.
- 16.
See p. 46 of: http://persmin.gov.in/DOPT/Brochure_Reservation_SCSTBackward/Ch-06_2014.pdf (accessed 20 October 2018).
References
Bhambri, C. P. (2005). Reservations and Casteism. Economic and Political Weekly, 40, 806–808.
Borooah, V. K. (2001a). How Do Employees of Ethnic Origin Fare on the Occupational Ladder in Britain? Scottish Journal of Political Economy, 48, 1–26.
Borooah, V. K. (2001b). The Measurement of Employment Inequality Between Population Subgroups: Theory and Application. Labour, 15, 169–189.
Borooah, V. K., Dubey, A., & Iyer, S. (2007). The Effectiveness of Jobs Reservation: Caste, Religion, and Economic Status in India. Development & Change, 38, 423–455.
Bourguignon, F. (1979). Decomposable Income Inequality Measures. Econometrica, 47, 901–920.
Cowell, F., & Jenkins, S. (1995). How Much Inequality Can We Explain? A Methodology and an Application to the United States. Economic Journal, 105, 421–430.
Desai, S., Dubey, A., & Vanneman, R. (2015). India Human Development Survey-II. University of Maryland and National Council of Applied Economic Research, New Delhi. Ann Arbor: Inter-university Consortium for Political and Social Research.
Dhesi, A. S., & Singh, H. (1989). Education, Labour Market Distortions and Relative Earnings of Different Religion-Caste Categories in India (A Case Study of Delhi). Canadian Journal of Development Studies, 10, 75–89.
Elmslie, B., & Sedo, S. (1996). Discrimination, Social Psychology and Hysteresis in Labour Markets. Journal of Economic Psychology, 17, 465–478.
Esteve-Volart, B. (2004). Gender Discrimination and Growth: Theory and Evidence from India. Suntory and Toyota International Centres for Economics and Related Disciplines. London: London School of Economics and Political Science.
Heilman, M. E., Block, C. J., & Lucas, J. A. (1992). Presumed Incompetent? Stigmatization and ‘Affirmative Action Efforts’. Journal of Applied Psychology, 77, 536–544.
Heilman, M. E., Block, C. J., & Stathatos, P. (1997). The Affirmative Action Stigma of Incompetence: Effects of Performance Information Ambiguity. Academy of Management Journal, 40, 603–625.
Ito, T. (2009). Caste Discrimination and Transaction Costs in the Labor Market: Evidence from Rural North India. Journal of Development Economics, 88, 292–300.
Jeffery, R., & Jeffery, P. (1997). Population, Gender and Politics. Cambridge: Cambridge University Press.
Leslie, L. M., Mayer, D. M., & Kravitz, D. A. (2014). The Stigma of Affirmative Action: A Stereotyping-Based Theory and Meta-Analytic Test of the Consequences for Performance. Academy of Management Journal, 57, 964–989.
Long, J. S., & Freese, J. (2014). Regression Models for Categorical Dependent Variables using Stata. College Station: Stata Press.
Macpherson, D. A., & Hirsch, B. T. (1995). Wages and Gender Composition: Why Do Women’s Jobs Pay Less? Journal of Labor Research, 13, 426–471.
Myrdal, G. (1944). An American Dilemma: The Negro Problem and American Democracy. New York: Pantheon.
Osborne, E. (2001). Culture, Development and Government. Economic Development and Cultural Change, 49, 659–685.
Riley, J. L. (2012, 7 May). Affirmative Action’s Stigma. The Wall Street Journal (Opinion).
Schmidt, P., & Strauss, R. P. (1975). The Prediction of Occupation Using Multinomial Logit Models. International Economic Review, 16, 471–486.
Shorrocks, A. F. (1980). A Class of Additively Decomposable Measures. Econometrica, 50, 613–625.
Theil, H. (1967). Economics and Information Theory. Amsterdam: North-Holland.
Thimmaiah, G. (2005). Implications of Reservations in Private Sector. Economic and Political Weekly, 40, 745–749.
Thorat, S., & Attewell, P. (2007). A Legacy of Social Discrimination: A Correspondence Study of Job Discrimination in India. Economic and Political Weekly, 42, 4141–4145.
Thorat, S., Aryama, & Negi, P. (Eds.). (2005). Reservation and Private Sector: Quest for Equal Opportunity and Growth. New Delhi: Rawat Publications.
Thorat, S., Tagade, N., & Naik, A. K. (2016). Prejudice Against Reservation Policies: How and Why. Economic and Political Weekly, 51, 61–69.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 The Author(s)
About this chapter
Cite this chapter
Borooah, V.K. (2019). Caste, Gender, and Occupational Outcomes. In: Disparity and Discrimination in Labour Market Outcomes in India. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-16264-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-16264-1_4
Published:
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-030-16263-4
Online ISBN: 978-3-030-16264-1
eBook Packages: Economics and FinanceEconomics and Finance (R0)