A deeper look into India’s employment landscape since the year 2000 throws some interesting questions regarding concerns on the gendered composition of the nation’s workforce. India’s male and female labor force participation rate (in the working age population category) has been on a persistent decline all over these years, and continues to be so. The male workforce participation rate reduced from around 64% to 49%, while female work force participation rate declined from 26% to 16% (2000-2015 period). These are numbers restricted to the limited sphere of organised, formal employment across India, which is not more than 20% of the overall employment landscape.

In a few analytical observations made over the last few years, this troubling trend has been widely discussed, and in much detail, acknowledges rise in female-male workforce inequality as a subject of grave concern, especially for an economy that continues to battle a macro-job crisis. The gravity of the problem, as we argue here, warrants a structural reorientation in terms of our employment and growth policies, both, now and in years to come.

The International Labour Organization (2018) states that – in India only 32.8% of women formally participate in the labor force-whereas men constitute 81.1%. Further, in recent years, quite mysteriously, the rise of male incomes across sectors have been followed by a reduction in female labor force participation, particularly in urban areas. The proportion of women employed in the “vulnerable” employment category also remains extremely high, at around 80% of the overall workforce.

Figure 1: Female-Male Distribution of Employment Scenario (LFPR vs. Vulnerable Employment Ratio in %) Source: Author’s calculations from World Bank Database
Figure 1: Female-Male Distribution of Employment Scenario (LFPR vs. Vulnerable Employment Ratio in %) Source: Author’s calculations from World Bank Database

What is interesting to observe is how most changes to the female-male labor force participation have largely been shaped by the gendered, sectoral growth of employment in India, where, most growth in employment has been seen in low-skilled service industry and construction (where gender inequality is highest). Growth in the medium to high-skill (white-collar) service industries has been insufficient to draw in more working-age women over recent years (see Figure 2). Most employment growth in areas of construction, manufacturing, trade & transport have widened the female-male workforce participation divide, whereas, in areas such as health, education and IT (seeing a more balanced participation rate), maintaining a balanced workforce participation still lacks priority in terms of growth policy focus.

Figure 2: Female-Male Sector Wise Workforce Participation (%) Source: Author’s calculations from World Bank Database.
Figure 2: Female-Male Sector Wise Workforce Participation (%) Source: Author’s calculations from World Bank Database.

To address this simply as a concern stemming from lack to educational opportunities is unfair. An exclusive focus on improving the education enrolment rates for women – as important as it may be, has proven to be partially successful strategy in reducing both, the rising gendered nature of inequality in wage-gap and their sector-wise workforce participation rate (vs. males). As discussed earlier, the low female enrolment in secondary and tertiary levels of education (vs. males) also affects and shapes the employability scenario for women and their employment expectations (which is hardly discussed).

Another critical area to understand is its burgeoning care economy where maximum female employment participation remains endowed with a high degree of unpaid work (often in the unorganised, informal base). There is a sector-wise distribution of such unpaid work, where, particularly in the agricultural work, work of most women remains highly undervalued, underpaid, and detrimental to their participation in paid labor. Large-scale informal nature of their employment further exacerbates this issue from a statistical perspective. Women in agriculture are expected to provide nutrition, partake in subsistence agriculture, perform eldercare – with an average of 25 hours a week spent on household work, and 5 hours in care and community work, women are afflicted by significant time poverty in India.

Data shows that despite this, women and men spend an equal average time in agricultural work. Not only is this economically relevant to a lapse in productivity, it further affects the family environment which has generational effects – daughters of women in such situations typically must either aid with or perform an equivalent quantity of unpaid work, thus increasing the opportunity costs for their time in school, leading to compromise in the attainment of skills (see Figure 3). Empirically observed, this leads to a reduced quality of human capital and skilled workforce in the future, affecting aggregate growth capacities.

The care economy’s relevance prompts a reevaluation of the aggregate value of “work” itself, especially in the future outlook of employment policies. It is important not to see this as an Indian problem either. As per a 2019 Oxfam report, a woman, on an average still spends more than 5 hours on unpaid work each day as compared to the average man who spends about 30 minutes on similar (household) work. It showed that the unpaid labor of women accounts for 3.1% of the country’s GDP. With one of the largest pay gaps in the world, where women earn around 25% lesser than men as of 2016, a considerable focus is required on understanding the gendered distribution of workforce in employment participation as well as in distribution of earnings, and thus, remains critical in India’s growth context and policy-landscape.

Figure 3: Female-Male Youth Unemployment vs. Female-Male Contributing Family Workers Source: Author’s calculations from World Bank Database
Figure 3: Female-Male Youth Unemployment vs. Female-Male Contributing Family Workers Source: Author’s calculations from World Bank Database

It is critical to understand that womanhood is an identity with multiple vulnerabilities attached to it. These vulnerabilities are not shaped from a result of varying economic circumstances but from evolving social norms, government policies, and patriarchal oppression. George Akerlof and Rachael Kranton in their canonical work on identity economics argue how: “people have identity-based payoffs derived from their own actions; people have identity-based payoffs derived from others’ actions; third parties can generate persistent changes in these payoffs, and some people may choose their identity, but choice may be prescribed for others”. Divided across the social layers of caste and class, women in India often suffer more from such identity-based payoffs i.e. less from their own actions and more as a result from the actions and influence of others.

To tackle such identity-based payoffs, growth policies in India require a structural reorientation in their very outlook. Gender-balanced sectors of employment (say, in healthcare and education) needs much more public support for increasing female-male employment participation. At the same time, other sectors (IT, Accommodation, Manufacturing, Construction etc.) need an exclusive focus on enabling a more gender-inclusive employment landscape (even employing women-reservation in public sector spaces). Structural shifts are required from women to move out from vulnerable areas of occupations say, from agri-based employment in rural areas to organised manufacturing and service industries. Greater upward social and income mobility for women thus, require a comprehensive macroeconomic policy focus with the right set of incentives for maximising female-employment expectations.

At the same time, the gendered methodology of (employment) data extraction also requires a categorical focus on capturing other gendered groups-the LGBTQ community-in highlighting their own “vulnerabilities” and challenges i.e. in terms of lack to employment opportunities in the organised workforce. Most employment data in India, gives very little information on the participation of LGBTQ community in both public and private sectors. Concerns regarding jobs and better quality jobs require a fundamental restructuring of employment data collation.

Our analysis here thus, contemplates a feminist reimagination of growth which paves the way for gender non-binary approaches to workforce participation and wage distribution. The LGBTQ and specifically transgender community’s role in the economy requires focused data collection, the absence of which hinders a holistic survey of the Indian economy. Over time, it is hoped that such data and growth analysis can enable a more gender-inclusive growth policy, focusing on the disproportionate sectoral distribution of the work force; increasing the employability of women and other vulnerable gender groups with a comprehensive focus on education and skilling (secondary and tertiary levels); and, developing a deeper understanding of the care economy with a need for minimising (female) unpaid work-and see these as part of core employability issues. These concerns do no quality merely as part of the core economic problems affecting India, but, are as Martha Fineman states, about the “inter-connection and cross-fertilisation between feminist economics, feminist legal theory, theorisations of care, care-work and dependency, in philosophy as well as comparative welfare state research, and the reinvigoration and new theorisations of human rights”.

Views are personal.

Deepanshu Mohan is assistant professor of economics, and director, Centre for New Economics Studies, O.P. Jindal Global University. Srivatsan Manivannan is a graduate from Jindal School of Liberal Arts and Humanities.

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