The workforce participation rate of India’s women is significantly lower than that of the men; and amongst the women, the employment levels of urban women are lower than those of their rural counterparts. Using the findings of the 2018 Periodic Labour Force Survey (PLFS), released in 2019, this brief provides an overview of the current state of female labour force participation in urban India. It analyses data on vocational training and employment, education and employment, rural versus urban employment, and employment in social groups. The brief makes recommendations for arresting the decline in urban women’s inclusion in the workforce. It outlines the ways in which the skilling, education, and labour departments can work together to skill the labour force in the jobs that are commensurate with education levels, and also diversify the areas in which the skilled and educated candidates can work.
Attribution: Aditi Ratho, “Promoting Female Participation in Urban India’s Labour Force,” ORF Issue Brief No. 348, March 2020, Observer Research Foundation.
Following India’s independence, the country’s labour history viewed issues of gender as superfluous; the fact that there were low proportions of female workers was irrelevant to the holistic and all-encompassing stories of caste and class mobilisation. Some decades later, the 1980s would see a renewed surge of feminisation of labour activity period in which labour and social rights became perceived increasingly as costs and rigidities. Since then, development policies in India have tended to centre more on women’s reproductive rather than productive roles, as shown by the amount of investment in population and family planning programmes that in turn have created a positive impact on women’s employment.
Maternal and child health has been an integral part of the Family Welfare Programme of India since the time of the First and Second Five-Year Plans (1951-56 and 1956-61), with the objective of “reducing the birth rate to the extent necessary to stabilise the population at a level consistent with the requirement of the national economy.” The National Population Policy adopted by the Government of India in 2000 reiterated the government’s commitment to safe motherhood programmes within the wider context of reproductive health.
Historically, therefore, India has viewed women primarily for their reproductive role. Such rigid gender assignment has acted as an impediment to employment. A study conducted in 2018 by researchers at Harvard Kennedy School, shows that female labour force participation drops among women in “their early to mid-twenties in urban areas, suggesting that marriage and family-related responsibilities may specifically limit women’s labour force participation.” For women who do find productive employment, it is more difficult to get adequate remuneration compared to their male counterparts. The Monster Salary Index, released in 2018, revealed that between 2015 and 2017 the gender pay gap in India remained at 24.3 percent on average in the man’s favour; “as long as there exist [social] norms against women’s market engagement, we expect to see…gender wage gaps that cannot be explained.” For example, as employers anticipate that their female employees will eventually file for maternity leave during their tenure, they offer these women lower wages.
In labour economics, “human capital corresponds to any stock of knowledge or characteristics the worker has (either innate or acquired) that contributes to his or her productivity.” Within this field, the “Becker-Mincer” wage equation developed in the 1970s considers human capital variables of “education, proxied by years of schooling, work experience (proxied by age minus the years of schooling minus six years) and the square of experience,” to determine a person’s earnings. Research conducted by Kaur et al shows that the “experience” component in the equation for women with children involves an error, where for the same age and education, women have less work experience comparable to men due to withdrawing from the workforce for an expected two years for childbearing.
Table 1 shows the wage loss for women, using a “human capital wage model” keeping education level constant, and with different ages of a woman inserted in the equation.
Table 1: Wage loss for women, compared with men of same education level and age
|Number of Children||Age (used to solve for work experience)||Withdrawal from labour force||Wage loss (as compared to male with same education level and years of experience)|
|1||30 years||2 years||6.3 percent less|
|2||35 years||4 years||10.4 percent less|
|3||40 years||6 years||11.9 percent less|
Source: Surjit S. Bhalla and Ravinder Kaur, “Labour Force Participation of Women in India: Some facts, some queries,” LSE Asia Centre Working Papers, (2011):
In India, the 2017 Amendment to the Maternity Benefit Act of 1961 seeks to promote women’s participation in the workforce by providing beneficial entitlements to female employees, like increasing maternity leave from 12 weeks to 26 and ensuring that every establishment with over 50 employees has a crèche service. The law was designed to ensure women’s participation is not hindered due to childbearing duties. Still, there must be laws to protect women from wage calculations of hiring for so-called ‘lost experience’ due to childbearing and infrastructural costs.
Sweden, for instance, has a “Parental leave Act” that gives both parents leave – these egalitarian measures would eventually lead to egalitarian wages as the lost experience accrues for both parents. Researchers at the Stockholm University showed that “lower earnings following parental leave are well-documented across countries for women as well as for men.” Between 1990 and 2013, total fertility rate in India fell from 4.0 to 2.5 children per woman. The decreasing fertility means childbearing is not as much of a constraint to labour force participation. However, despite economic growth and decline in fertility rate, “India’s women are conspicuously absent from the labour force.” Analysts agree that women in India still face “legal, normative, and economic constraints to work.” Various laws in India purport to help women succeed in the workplace; their effect, however, is the opposite. For example, to ensure women’s safety, Section 66(1)(b) of the Factories (Amendment) Act of 1987 states that “no woman shall be required or allowed to work in any factory except between the hours of 6 a.m. and 7 p.m.” Female participation in export-oriented manufacturing jobs fell in the 1990s despite increased trade and reduced trade barriers during the same period, which were likely due to legal constraints on women’s working hours through the factory laws.
This fall in export-oriented manufacturing jobs, which has coincided with the rise in female self-employment in the manufacturing sector, shows employer trends of wanting workers for extended hours, but not willing to bear the costs of alleviating risk in the workplace for female workers. Home-based workers are disguised wage workers as their employers seek to avoid risk-reducing arrangements such as job security and social insurance benefits. Nearly one-third (31.7 percent) of women in the non-agriculture sector were home-based workers, compared to 11 percent of men. The Periodic Labour Force Survey (PLFS) of 2018 tracks the number of workers in the informal sector, among the workers in the non-agriculture sectors and relevant agricultural sectors (such as animal production, aquaculture, fishing, and support activities to agriculture). According to the survey, among female workers, informal workers accounted for 54.8 percent of the workforce. Even if an individual is engaged in salaried labour, they do not fall into a formal employment structure unless the requisite employee benefits and contractual arrangements are attached.
In India, more women work without these employee benefits than men. In 2017-18, among regular wage/salaried employees in the non-agriculture sector, 49.6 percent of the workers were not eligible for any social security benefit: 49 per cent among males and 51.8 percent among females. In the rural areas, the proportion of regular wage/salaried employees who were not eligible for any social security benefit was 51.9 percent among male regular wage/salaried employees, and 55.1 percent among female regular wage/salaried employees. In the urban areas, 47 percent of the male salaried workforce were not eligible for any social security benefit, with 50.1 percent women making up the share that were not eligible for any social security benefit.
The government is trying to protect these informal workers through schemes like the Pradhan Mantri Shram Yogi Maan-dhan (PM-SYM) which provides social security via a pension plan to the unorganised sector. However, these initiatives cause employers to relax on their responsibility of providing benefits and entitlements to their employees. Since the statistics show that female informal employment is higher, and females are less likely to have security benefits in jobs, schemes such as the PM-SYM—while well-meaning—may further disincentivise employers from providing the required employee benefits.
As mentioned earlier, it is easier to place women in the informal sector as employers do not have to shoulder the burden of “insecure, unsafe and unhealthy work conditions.” Jobs are moving from the agricultural sector to the manufacturing and tertiary sector; however, the migration trends from rural to urban are still largely viewed as a male domain, without adequate policymaking to ensure a woman’s entry into the urban market. The rising female rural to urban migration—called the ‘feminisation of migration’— must be reflected in urban planning. A corollary imperative is that the different experiences and needs of women around access to water, sanitation, safe transportation and streets, health, education and care facilities must be considered. This would help ensure that more women are able to secure access to the labour market.
Determinants of Female Labour Force Participation
According to the United Nations Development Program’s (UNDP) “India Skills Report” of 2019, 68.3 percent of women graduates in urban India are not in paid jobs. The International Labour Organisation (ILO) ranked India’s female labour force participation rate at 121 out of 131 countries in 2013, one of the lowest in the world, and there has been a drastic decline in FLFP from 1990 to 2016.
A seminal study analysing India’s “missing” labour found that a large proportion of the country’s women were not in paid labour and instead confined to unpaid domestic activities, even as overall, the degree of social mobility in the country has increased over time. In another study, which builds on data from the 2011 NSSO survey, the analysts identified “missing female labour” as the single most important component that accounted for the decline in aggregate labour force.
Meanwhile, the PLFS indicators on the employment levels of different social groups show that labour force participation was highest for ST (41.8 percent), followed by SC (37.6 percent), and OBC (36.2 percent). Participation was lowest among the ‘others’ (35.9 percent). In urban areas, among females, labour force participation was highest for SC (19.2 percent) and the lowest for ‘others’ (14.2 percent). These statistics underscore the correlation between women’s socioeconomic status and their participation (or lack of it) in the workforce: as deprivation decreases, more women are dropping out of the labour force.
While education is assumed to provide women with empowering qualities like greater mobility in public spaces, and greater control over their own lives, the “transition from being educated to becoming a paid worker is not automatic” due to reasons such as “a lack of awareness of opportunities and role models.” Therefore, there is little correlation between education and empowerment, and work and empowerment.
Even as the number of urban women in higher education has increased from 46.5 percent in 2004-2005 to 65.4 percent in 2017-2018, the proportion of highly educated women who work was still only 17.3 percent in 2017-2018. These statistics reiterate the idea that while education might lead to a sense of empowerment in that women can work, it does not automatically translate into labour force participation. In the recent PLFS data comparing the urban Worker Population Ratio (WPR) with education levels, it is seen that WPR is low for women across all categories of education.
Table 2: Urban WPR, 2017-2018 (15 years and above; in percent)
|Level of Education|
|Not literate||literate/up to primary||Middle||Secondary||Higher secondary||Diploma/certificate course||Graduate||Post- graduate and above||Secondary and above||All|
Source: “Annual Report, Periodic Labour Force Survey 2017-2018”, page 61
As seen in Table 2, the WPRs for female adults that are ‘not literate’ and ‘literate/up to primary’, and those that have an education level of ‘graduate’ and ‘secondary and above’, are at similar levels: 21.6 percent, 21.7 percent, 22.8 percent, and 17.3 percent, respectively. Thus, there is no positive correlation between level of education and employment. The low unemployment rate for the less educated urban women could be a result of them being absorbed in the informal sector, which offers lower remuneration. Analysts reckon that the reason that graduates in India’s urban cities voluntarily drop out of the labour force is the stigma associated with working in jobs that require lesser qualifications. The lowest WPR in females is the middle-run of education qualifications, where one is too educated to be in the informal sector, but not educated enough to have a job requiring a formal qualification.
A skills training agenda by itself, as it stands today, may be inadequate to address the employment concerns of this demographic group. Technical and vocational education and training is understood as comprising education, training and skills development relating to a wide range of occupational fields, production, services and livelihoods. The main objective of this form of training is to make individuals employable for a broad range of occupations in various industries. However, there has to be a shift in paradigms to shed the popular notion that vocational training institutions are only for individuals with lesser academic abilities. The asymmetry in reputation of the vocational training institutes and thus the aspiration of trainees, which may be the cause for the dip in labour force participation for educated women, can be overcome if skills development is brought into mainstream education and there is no watertight segregation between the kinds of courses offered by colleges and vocational training institutes. After all, one of the outcomes expected from the implementation of the National Skills Qualification Framework (NSQF)[a] is “mobility between vocational and general education by alignment of degrees with NSQF.” This goal must be pursued with systematic vigour.
As seen in Table 3, for both formal and non-formal vocational training, a higher percentage of males compared to females have received vocational/technical training.
Table 3: Percentage of Urban Males and Females Receiving Vocational and Non-Vocational Training
|Received formal vocational training (%)||Received non-formal vocational training (%)||Did not receive vocational training (%)|
Source: “Annual Report, Periodic Labour Force Survey 2017-2018”, page 87
The field of vocational training that men and women receive signifies the specific area of training that a person obtained. Table 4 shows the data for which field of vocational training men and women received.
Table 4: Field of Training in Vocational Training: Urban Males and Females (in percentage)
|Urban Female||Urban Male|
|Office/Business related work||0.2||1.1|
|Work related to childcare, nutrition, pre-school, crèche||18.9||1.2|
Source: “Annual Report, Periodic Labour Force Survey 2017-2018”, page 87
From the above data, and those for 21 sectors of vocational training shown in the PLFS, it can be seen that more men than women received training in 20 of the 21 sectors, including those that are seen as a traditionally ‘female domain’, like handlooms and apparels. The only sector which shows a larger number of women getting training, is work related to childcare, nutrition, pre-school, and crèches.
This data shows a clear need to balance mobilisation strategies to train more women and retain them in the sector. To create a better distribution of vocational training courses, it is imperative to undertake robust Skills Gap Analyses (SGA) across states. This will show which sectors require the establishment of specific training centres with regards to existing employment opportunities. The SGA reports must not only provide statistics regarding human resource requirements across various employment sectors in urban areas; they should also reveal how many skilled beneficiaries (both male and female) have been employed and absorbed within these sectors. Volatility in the economy is reflected in the domestic labour market; therefore, the changes in jobs shown through these studies, and the absorption capacity of these sectors need to be reflected in the courses offered.
Furthermore, a gendered and disaggregated study needs to be done to assess which sectors are averse to a particular gender, so that policymaking can be adapted to ensure appropriate and equitable employment generation tools in the area. Though women’s labour force participation in India’s urban workforce for women of all ages has risen slightly from 15.5 percent in 2011-2012 to 15.9 percent in 2017-2018, paid employment for women does not necessarily correlate with women’s freedom and agency, especially when an increasing workforce might still be constrained within a narrow scope of what constitute ‘feminine’ jobs. Large numbers of women workers are overcrowded into a small number of ‘female occupations,’ driving female wages down.
It is essential to adopt not only a gender-agnostic approach in developing vocational training courses, but also a gender disaggregated strategy in skill gap analyses. Even if the skilling and labour departments are made to diversify courses in vocational training, employers need to accept women in these new roles. For example, in urban areas, among females who received formal training, 38.6 percent were employed, 10 percent were unemployed, and 51 percent were not in the labour force. Therefore, it is essential to focus on retaining and handholding women once they are trained, to create employment following vocational training.
Table 4 shows that the only sector where there is a larger number of women obtaining some form of training, is work related to childcare, nutrition, pre-school, and crèches—once again reiterating the gendered assignment of roles even in vocational trainings. However, since total fertility rate has fallen from 4.0 to 2.5 children per woman, and life expectancy has increased, simply restricting vocations to childrearing and child-related jobs can change to an ‘age-related care economy’ where women are able to provide support to age-related disabilities as home-care workers, paramedics, and nurses.
Infrastructure and gender-disaggregated beneficiary data for Women-Centric Employment Generation
The concept of “Gender-Budgeting” was introduced in India in 2001, not as an accounting exercise, but “but an ongoing process of keeping a gender perspective in policy/ programme formulation, its implementation and review.” This is a form of planning and budgeting that ensures that “policy prescriptions to alleviate inequality are translated into outputs and outcomes by linking them to budgetary allocations.”
The Ministry of Women and Child Development, Government of India, has outlined mechanisms that can be used for operationalising and institutionalising gender budgeting. These include gender-responsive policy appraisal, reporting a Gender Budget Statement, capacity building of government officials, generating outcome budgets, and conducting impact assessments and audits.
A targeted exercise to collate infrastructure data directly related to a woman’s presence in the workspace must be created to undertake a holistic assessment of the impact and formulate potential remedies. It is imperative to determine on-ground numbers on the availability of toilets, nursing homes, renting accommodations, and crèches in the workplace.
Research in India shows that “women have more access to public spaces in mixed use areas, where shops and business establishments are open late into the night, ensuring activity at all times.” However, a “default response from decision makers when the provision of adequate infrastructure for women is discussed” is that there are not enough women in public spaces to warrant it. Therefore, it should be a prerogative to create the infrastructure required to initiate access to public spaces and places of employment. Policies should focus on making infrastructure safe for women, regardless of whether women will work in the space or not. Physical factors such as space and lighting, and social factors such as awareness and capacity building are major determinants of how safe and inclusive public spaces are. Architects, engineers, and urban planners must work together to generate innovative ideas and discussions surrounding gender-sensitive infrastructure planning and gender-based analyses of spaces. The discourse should include issues such as dispensation of civic amenities, and creation and maintenance of civic infrastructure. These will have to be considered in the budget-making, planning, and execution stages.
Apart from infrastructure data to gauge access to workspace, gender-disaggregated beneficiary data in the form of gender budgeting is also important to understand the distribution of funds amongst men and women. The question is whether there is a gender gap in public funding, and if these gaps affect the provision of opportunities for a certain gender.
The Skills Acquisition and Knowledge Awareness for Livelihood Promotion (SANKALP) project, announced in July 2019, has some remarkable recommendations that illustrate the concerted effort being made by the government to re-evaluate the lesser performing elements of the previous skilling cycle. The SANKALP’s proposal to set up a National Skills Research Division within the NSDA is also a welcome move. The research centre will be an independent think tank that will analyse labour market trends, undertake impact evaluation of skill development programmes, and provide policy inputs to all related bodies in skill development. State-level analyses of gaps in skills conducted by NSDA should have a male-female segregation to see whether jobs are distributed evenly, and evaluate the impact of gender-segregation of vocational courses on employment opportunities. Therefore, the gathering of relevant data on gender-segregated budgeting as well as gender-segregated courses must be done to see how it affects employment numbers.
Vocational courses should account for the future of work. According to the India Skills Report 2019, 40-50 percent of “existing jobs which are transaction heavy will get automated”—e.g. financial services, manufacturing, transportation, packaging, and shipping. Courses need to offer both men and women skills in new technologies like “auto analytics engineers” and “sustainability integration experts.” Existing companies, to prevent job loss, must initiate mandatory immersive programs to help employees acquire new digital skills.
An area worth the government’s attention is the expanding e-commerce space, where an increasing number of women are participating as internet and technology companies grow. Research on the role of e-commerce in generating female employment shows that 20 percent of total online sellers in the marketplace are women, which has created a spike in entrepreneurship. Furthermore, online portals such as Mahila-e-haat are expected to benefit around 10,000 self-help groups and 1.25 lakh women. Institutes providing vocational training courses need to tap into this surge in gender-agnostic employment choices, and states should create opportunities for the skilling of women in these areas, including entrepreneurship, without prejudice. Efforts to provide social security to informal labourers, as discussed previously, must account for these burgeoning semi-informal workers who may not have official contract-based jobs.
The ‘feminisation of labour’ is a phenomenon where there is a palpable rise in female labour force participation alongside a fall in men’s participation; moreover, a higher number of females are entering certain jobs that are traditionally the ‘domain’ of men. This is recently being seen in India. Another emerging pattern is that jobs with lower wages seem to be increasing with female participation.
India needs to nurture an environment where women, whether in formal or informal labour, are given the appropriate employee benefits and risk-free working environment. To ensure that educated women are a significant part of the workforce and that the skilling programmes are effective in generating employment in urban areas, policymakers must formulate strategies towards the diversification of jobs. Publicising female role models, and creating a healthy, safe, and hygienic work atmosphere would go far in dissolving the taboos and insecurities associated with women working. If these issues are included in a gendered form of budget and policymaking, female labour force participation in India can become a more hopeful aspiration.
[a] The National Skills Qualifications Framework (NSQF) is a competency-based framework that organizes all qualifications according to a series of levels of knowledge, skills and aptitude
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 Erin Fletcher, Rohini Pande, Charity Troyer Moore, “Women and Work in India: Descriptive Evidence and a Review of Potential Policies,” Harvard Kennedy School Faculty Research Series, (January 2018): 7
 Wage Indicator Foundation, “Monster Salary Index,” Wage Index Report India, (March 2018): 18
 Surjit S. Bhalla and Ravinder Kaur, “Labour Force Participation of Women in India: Some facts, some queries”, LSE Asia Centre Working Papers, (2011):12.
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 Erin Fletcher, Rohini Pande, Charity Troyer Moore, “Women and Work in India”, 2
 Ibid, 3
Erin Fletcher, Rohini Pande, Charity Troyer Moore, “Women and Work in India”, 14
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 “Annual Report, Periodic Labour Force Survey 2017-2018”, 91
 Annual Report, Periodic Labour Force Survey 2017-2018”, 61
 Worker Population Ratio (WPR) is defined as the percentage of employed persons in the population
 Rishi Kumar, Shravanth Mandava, Venkata Gopanapalli, “Vocational Training in India: Determinants of Participation and Effect on Wages”, Empirical Research on Vocational Education and Training 11 no.3 (2019).
Annual Report, Periodic Labour Force Survey 2017-2018”, 87
“Annual Report, Periodic Labour Force Survey 2017-2018”, 53
 Bhalla, S. Surjit and Kar, Ranvinder, “Labour Force Participation of Women in India: Some facts, some queries”
 “Annual Report, Periodic Labour Force Survey 2017-2018”, 89
 Erin Fletcher, Rohini Pande, Charity Troyer Moore, “Women and Work in India” 2
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 “India Skills Report,” United Nations Development Programme (2019): 22