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Gender Discrimination in Wage Earnings: A Study of Indian Wage Market

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  • Mitali Chinara

    (Utkal University)

Abstract

The fact that globally a gender gap exists along axes of economic, social and political outcomes is well documented. Studies have shown such gaps to be increasing or decreasing, changing by varying degrees, varying by magnitude depending on the period of study and region of analysis. The World Economic Forum’s Global Gender Gap Report shows tardy progress on closing the gender gaps along multiple axes. The report states that even while the global gender gap has become smaller since 2006, the extent of its closure is a measly four per cent; if this trend were allowed to perpetuate, it would take over a 100 years for the world’s women to be on par with men. India has tightened its gender gap by 2% in a year, which now stands at 68% across the four pillars of economy, education, health and political representation. The major improvement, however, has been witnessed in the arena of education, where the gaps in primary and secondary education have been completely eliminated. In the economic sphere, much work remains to be done. In so far as ensuring gender equality continues to be one of the objectives of Sustainable Development Goals, lack of it constitutes a challenge. Such gap is, however, either on account of inputs or characteristics that are different across members of different genders (the explained gap) or on account of differential premium on possession of comparable characteristics across genders (the unexplained gap). Decomposition of such gaps into their explained and unexplained fractions is important for the purpose of measuring the precise extent of gender discrimination. This paper fills a void in the existing literature by analysing such gaps in the wage market across select states of India. The paper uses the technique of Blinder–Oaxaca decomposition for the purpose of study, which has not been applied so far in studying inter-state characterization of gender wage gaps. Thereafter, the paper compares the results obtained for pooled wage market of India with results for urban and rural wage markets.

Suggested Citation

  • Mitali Chinara, 2018. "Gender Discrimination in Wage Earnings: A Study of Indian Wage Market," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 61(1), pages 157-169, March.
    • Handle: RePEc:spr:ijlaec:v:61:y:2018:i:1:d:10.1007_s41027-018-0132-5
    DOI: 10.1007/s41027-018-0132-5
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    References listed on IDEAS

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    1. Geeta Gandhi Kingdon & Jeemol Unni, 2001. "Education and Women's Labour Market Outcomes in India," Education Economics, Taylor & Francis Journals, vol. 9(2), pages 173-195.
    2. Shantanu Khanna, 2012. "Gender wage discrimination in India-- Glass ceiling or sticky floor?," Working papers 214, Centre for Development Economics, Delhi School of Economics.
    3. Ben Jann, 2008. "The Blinder–Oaxaca decomposition for linear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 453-479, December.
    4. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    5. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    6. Bhaumik, Sumon Kumar & Chakrabarty, Manisha, 2009. "Is education the panacea for economic deprivation of Muslims?: Evidence from wage earners in India, 1987-2005," Journal of Asian Economics, Elsevier, vol. 20(2), pages 137-149, March.
    7. Vani K. Borooah, 2005. "Caste, Inequality, and Poverty in India," Review of Development Economics, Wiley Blackwell, vol. 9(3), pages 399-414, August.
    8. Cotton, Jeremiah, 1988. "On the Decomposition of Wage Differentials," The Review of Economics and Statistics, MIT Press, vol. 70(2), pages 236-243, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Blinder–Oaxaca; Decomposition; Gender; Wage gap;
    All these keywords.

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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