In October 2014, Satya Nadella, the Microsoft CEO, said in an interview that women needed to trust karma if they don’t get the pay raise they want. “It’s not really about asking for a raise, but knowing and having faith that the system will give you the right raise,” he said.
The statement was widely criticised in the media and by women’s groups, leading to a quick apology from Nadella. It brought to the fore a fundamental question about how labour markets function, especially towards members of disadvantaged and marginalised groups.
So, should women “have faith” and hope for their rewards to improve? If labour markets do not recognise and appropriately remunerate their worth, is it just a case of bad luck, or of labour market discrimination?
To find the answers to these questions, we analyse the issue of gender parity in wages by focusing on the evolution of male-female wage gaps for India.
We use nationally representative data from the Employment-Unemployment Schedule (EUS) of two large rounds of the National Sample Survey (NSS) for 1999-2000 and 2009-2010, respectively, in order to explore gender wage gaps among regular wage/salaried (RWS) workers.
We focus on the most recent decade, as this has been a period of rapid growth, new job openings, greater integration with the global economy, and increasing domestic privatisation in India. While this study is not a causal analysis of these changes on gender wage gaps and gender discrimination, it raises questions about the likely association between these structural changes and wage disparities, and more broadly about discrimination.
Prior to analysing gender wage gaps is the issue of gender difference in access to the coveted RWS jobs that constitute a little more than 15% of the Indian labour force. In this small group of workers, women constituted only 18% in 2009-10 and only 13% of all women workers are in RWS jobs. Over the 10-year period, the educational and occupational profile of women improved relative to men. But in both 1999-2000 and 2009-2010, average female wages were less than for males with similar profiles, with the raw gender wage gap being 49% in 2009-2010.
Using a well-established technique in the discrimination literature, we break-up this gap into two components in order to see how much of the wage gap is due to different male-female wage-earning profiles (e.g. education, qualifications), and what part of the gap cannot be so explained. The latter—unexplained—part is conventionally seen as an indicator of labour market discrimination.
We show that the bulk of the gender wage gap at the mean is unexplained, i.e. possibly discriminatory. While average wage-earning attributes for women improved over the decade, the discriminatory component of the wage gap also increased. In fact, in 2009-2010, if women were “paid like men”, they would have earned more than men on account of their superior attributes.
For both 1999-2000 and 2009-2010, male wages are higher than female wages at all levels of wages. In both years, men and women employees at the lower levels saw greater disparities in wages than those at the higher-wage levels.
Thus, in contrast to the glass ceiling observed in much of the developed world, we see the existence of a “sticky floor” in India, in that gender wage gaps are higher among lower earning workers and steadily decline towards the higher end of the wage distribution.
This is true for all RWS worker, as well as separately for rural and urban workers. Using standard definitions, we find that the sticky floor became “stickier” for RWS women over the decade. Breaking up the wage gap into explained and unexplained parts, we find that not only is the bulk of the gender wage gaps discriminatory, but that the discriminatory component is higher at lower ends of the distribution.
In India, social norms place the burden of household responsibilities disproportionately on women. Because of this, men are perceived by employers to be more reliable vis-à-vis women. Also, given the higher probability of dropping out of the labour market (for childbearing and rearing), employers discriminate against women when they enter the labour market because they expect future career interruptions. As women move up the occupation structure and gain job experience, employers become aware of their reliability and may perhaps discriminate less.
Another reason for the sticky floor could be that the nature of jobs is very different at the two ends of the distribution. Women working at the upper end are more likely to be the urban educated elite, working in managerial or other professional positions. These high-wage earning women are more likely to be aware of their rights and might be in a better position to take action against perceived discrimination. Also, whether in the public sector or the private sector, most high paying jobs will have written contracts with predefined clauses for basic increases in salaries, year on year, thus making it harder to discriminate across genders.
Contrast this to a situation where an employer is paying a regular wage to a woman with no education working in an elementary occupation, a typical example of a worker at the bottom of the wage distribution in the Indian context. It is easier for the employer to discriminate in this case, as these jobs might be outside the jurisdiction of labour laws.
Article 39 of the Indian constitution envisaged equal pay for equal work for both men and women. To this end legislations such as the Equal Remunerations Act (1976) were enacted. However, considering that the minimum wage laws are often flouted, the gender wage gaps at the bottom of the distribution could be larger.
Thus, even in the highly selective, presumably meritocratic regular wage salaried jobs, women are discriminated, with a clear “sticky floor” effect: low-wage earners facing larger gaps in wages, as well as greater discrimination than better paid women.
Ashwini Deshpande and Deepti Goel are faculty at the Delhi School of Economics. Shantanu Khanna teaches economics at the Lady Shri Ram College, University of Delhi.
We welcome your comments at email@example.com.