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Reimagining India's Female Labour Force Participation: A Policy Review

Updated: Feb 1, 2022



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Overview


Female participation in the labour force, when compared to male participation, is often lower across countries. For India, however, it is significantly lower than its counterparts in Asia. As an emerging economy, these low rates remain a major cause of policy concern. To understand the root cause of the problem it is imperative to critically examine the definition of the term ‘labour force’ and understand both the demand and supply side drivers. This paper is a study of the recent and historical trends across a range of parameters including the COVID-19 impact, policy execution, education, household income, internet access, and socio-cultural norms on the female labour force participation.



1. Definition of Female Labour Force


1.1. Understanding the Concept of ‘Labour Force’ and ‘Work’


Labour Force participation is defined as the state of being ‘economically active’. The definition of ‘labour force’ includes individuals who are currently employed either on a full time or part time basis or are not employed but are actively searching for employment. This means that students who are not employed and are not looking for any form of employment do not come within the gambit of this definition.

Any activity which leads to the production of goods or services which are consumed within the household are excluded from the definition of ‘work’ This may include the following activities:

-Preparation or serving of meals

-Cleaning, decoration, and maintenance of the dwelling

-Care and training of children

Even today, women continue to do majority of the housework in India.


According to the Organization of Economic Cooperation and Development (OECD), Indian women on an average performs nearly 6 hours of unpaid work each day.


After exhaustively including all possible forms of economic activities across both the formal and informal sectors, a significant number of ‘working women’ are still being excluded from the labour force statistics.


1.2. Female Labour Force Participation in India


Accroding to the rankings issued by a World Bank report, India is ranked 121st out of 131 countries in terms of the female labour force participation rate. Though women constitute 48.1% of the total population, as of 2020 they account for only 20.3% of the total labour force in India. This is worse in comparison to its neighbours such as Srilanka where the female labour force participation is around 35%.


In short four out of five women are not a part of the labour force in India. As per the global rankings of 2017-18 only 9 countries - Yemen, Iraq, Jordan, Syria, Algeria, Iran, Somalia, Morocco, and Egypt have a female labour force participation (FLFP) rate lower than that of India.



The low female labour force participation in India is partly attributable to restrictive cultural norms regarding women’s work, the wide gender wage gap, low female literacy rate and a lack of flexible policies for working women.


Gender discrimination starts even before a woman enters into the labour force through societal issues such as female foeticide and lack of access to quality education. This directly impacts the future job opportunities and pay scale which amplifies the existing gender divide in the labour force.


The gender gap in the labour force participation is approximately 53%. There has been a stagnation in the share of women-led companies in India. The proportion of CEO’s and Managing Directors of NSE listed companies who are women has increased in proportion from 3.2% in 2014 to a mere 3.7% in 2019. On assessing the hourly wages earned by women against that of men, women on an average earn 65.5% of what their male counterparts earn for performing the same work.


The Covid-19 pandemic has resulted in job stagnation and high unemployment rates for women, keeping them further out of the labour force. The wide gender divide within the labour force along with unequal distribution of unpaid work is responsible for the significant gender pay gap and underrepresenation of women in the workforce.


From the available data the historical labour force breakdowns for Rural Females and Urban Females as a percentage of the labour force and as a percentage of the total paid workers across the agriculture, manufacturing, construction, and services industries are populated below.


• The participation of Rural females and Urban females has declined over the past 4 decades from 85.5% to 80.2% and 21.2% to 11.5% respectively for the agriculture industry.

• The participation of Rural females and Urban females has increased over the past 4 decades from 6.9% to 8.9% and 49.2% to 58.2% respectively for the construction and services industry.

• The participation of Rural females and Urban females has increased over the past 4 decades from 7.6% to 10.9% and 29.6% to 30.3% in the manufacturing industry.

This is attributable to the rising per capita income in India since 1990.


 

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1.3. Importance of Female Labour Force Participation for the Indian Economy


The female labour force participation has macroeconomic implications as well. On basis of data from 2000-2004, the United Nations Economic and Social Commission for Asia and Pacific (ESCAP) has estimated th at if India’s female labour force participation reached at par with that of the United States (86%), its gross domestic product (GDP) would increase by 4.2% a year and growth rate by 1.08% representing an overall annual gain of $19 billion. A 10% permanent increase in female labour force participation would lead to an increase in growth rates by 0.3%.


By 2050, India will surpass China to become the most populous country in the world, with a total estimated population of 1.66 billion. An increase in female labour force participation by 10% points could add $770 billion to India’s GDP by 2025.


The Indian societal structure has traditionally revolved around a patriarchal family structure. There are several complex social issues which have a direct impact on the female labour force participation. Effective measures and policies need to be put in place if we want to accelerate development.


Each 10 years of education add approximately an extra 6.5% increase in the total labour force participation. High illiteracy rate among women and the prevailing social evils are a major obstacle in the roadmap towards achieving equal labour force participation.


Policy makers and government should ensure: -

1. Legislation provides equal opportunity for women and men and non-discrimination is actually practiced.

2. Women are the major beneficiaries of schemes under the financial inclusion agenda.

3. Grassroots monitoring to ensure the effective implementation of the policies.



2. Recent Trends and Impact of COVID-19


2.1. Variation in Female Labour Force Participation by state

Tamil Nadu, Himachal Pradesh, and West Bengal were the champions of FLFP while Bihar, Uttar Pradesh, and Jharkhand were the worst performers after Covid-19 hit.



48% of Indian population over the age of 15 are female and yet, the FLFP in India was only 18% before the pandemic, which dropped to 15% afterwards.


The two major factors driving this phenomenon are education and poverty rate.



2.2. Effect of lockdowns, curfews, and quarantines on Female Labour Force Participation in India


While 61 % of men followed the no effect trajectory over this period, the corresponding figure for women was only 19 %. Further, while only 7% of men followed a no-recovery trajectory, the figure for women was 47 %. Women were also much more likely to also experience a delayed job loss even after the lockdown relative to men.


According to a survey during the lockdown, 81% of the total population reported to avail no services of the domestic workers as compared to 13% before the lockdown. Therefore, the domestic work including cleaning, cooking, laundry, child-care, and elderly-care, which were earlier performed by the domestic workers for income, were now performed by the household members without any remuneration. This increased the burden of unpaid work for everyone, but more so by women.


This also resulted in a lot of women losing jobs since mostly women were employed as domestic help. In 2018, it was estimated that India employed 4.9 million people as domestic help, around 2/3rd of which were women, who ended up losing their job.


All frontline health workers at ASHA (Accredited Social Health Activists), ANM (Auxiliary Nurse and Midwife) and Anganwadi workers (the ICDS or Integrated Child Development Scheme workers), were women. This resulted in a lot of job losses during the pandemic and subsequent lockdown.


Industries with more women employees were already on a slower recovery path and saw a drop in demand under the second wave. Rural women work from home in sectors such as textiles and handicrafts are paid per piece, so this exacerbated their suffering. As lockdown restrictions eased and cases of Covid -19 reduced, supply and demand began bouncing back. Community-based organizations, which are a major purchaser from rural women, shared that they were planning to restart physical exhibitions in April/May 2021. Rural women restarted the production of Kurtis, shirts, bags, etc., moving away from mostly producing face masks. Such events had to be cancelled due to the second wave, leading to job and income losses for rural women.



2.3. Disruption in the participation of women in paid work due to Covid-19


Women were more likely to be burdened by unpaid work during the pandemic.


As a result of the lockdown, urban households had to manage without domestic helpers which resulted in an increase in hours spent on housework for both women and men when compared to December 2019.


This can be attributed to social norms because women are still expected to be the primary caregivers in the household. A lot of women also saw an increase in unpaid work because Work from Home and online education meant that a lot of family members like children and spouses were staying at home and dependent on the woman for household chores.

While this has resulted in increased burden and work hours for some women, others have had to quit their jobs to take care of their families. This was more prevalent in middle income households.


They also faced discrimination at work due to having this additional burden of responsibilities. In Q4 2020, WeWork launched a daily pass whereby people could work from their buildings spanning 6 cities in India. It was noted that over 40% of the users were women (Economic Times-2021), which suggested that women were finding working from home difficult.


This is not the case for all women. For few women, this was an opportunity which included women who had taken a career break to have children, get married or had to prioritise family responsibilities. Remote working helped them to get back in the labour force which was offering a slightly better work life balance.


During lockdown, remote working was not an option for most women especially for women in rural areas due to the nature of their work. The potential for remote working in the 3 sectors where women predominantly are employed in (Agriculture, Services, Manufacturing) is low if not nil.


The household income in urban India was adversely affected by Covid-19. Among other factors that have contributed to this statistic, a decline in female participation in employment plays an important role.


In the first month of the national lockdown, between March to April 2020, 15.4 million women lost their jobs, of which 12 million were rural women. Women, according to the CMIE, accounted for 10.7% of the workforce in 2019-20, but they accounted for 13.9% of the job losses in April 2020 when lockdown was enforced. By November 2020, while men recovered most of their lost jobs, CMIE estimates that 49% of the total job losses by November 2020 were of women. Despite this steep initial fall, rural women’s employment rebounded back to pre-Covid levels by July 2020.


Over the past year, urban women were pushed into rural work. Between March 2020 to March 2021, the number of women employed in rural areas increased by 9.6%, while those employed in urban areas fell by 19.6%. This shift was much lower amongst men, with male rural employment increasing by 0.8%, and urban employment falling by 0.3%.


As the second wave hit rural India, it left 5.7 million rural women unemployed in April 2021. Rural women formed nearly 80% of job losses in April 2021 compared to just 11% in April 2020. Some early signs of recovery were seen in May 2021, as nearly 2.8 million rural women returned to employment which is 11% of the rural female workforce.




3. Government Policies


Women’s labour force participation is determined by a confluence of social and economic forces at both the household and societal levels. Over the last four decades, the central government has tabled and enacted some landmark policies to facilitate an increase in the FLFP rates of India. While they include gender-sensitive components like gender quotas, maternity leaves, creche facilities etc., the gender biases of the d emographic expected to uphold these policies persist. Cultural norms and stigmas attached to women working outside and participating in economic activities are still rampant. The women workforce needs to be sufficiently freed from the disproportionate tasks of domestic work and maternity, provided with sufficient skills, adequate access to finance and safe working conditions. The labour market needs to be enabled to pay sufficient wages and have gender equal hiring practices. Finally, the quality of jobs needs to be assured in tandem with creating them. The following sections use both the supply and demand side drivers of FLFP to analyse some prominent Central Government policies that exist to enable growth in FLFP rates.


3.1. Creating Jobs


The rationale for these programmes is based on the premise that the government has an active role to play in promoting full employment in developing economies by assuming the role of the market maker for labour. (Antonopoulos, 2009)


3.1.1. Livelihood Interventions


Several government policies, while not envisaged as women empowerment acts, address the specific constraints faced by the female workforce and explicitly establish several gender-sensitive components, including gender quotas.

The Mahatma Gandhi National Rural Employment Guarantee Act 2005 (hereafter, NREGA) was passed by the Government of India as a public employment programme to provide a form of social security in rural areas by providing a basic income through labour intensive employment, while contributing to public assets.

Gender Dimensions: It mandates 1/3rd of all participants in the scheme be women, childcare facilities be provided at worksites and that men and women be paid equal wages. It also assures 100 days of work and low effort work closer to home for lactating and pregnant women. It mandates women be part of local committees for social audits, monitoring and vigilance. It also provides an unemployment allowance. Most importantly, it empowers women’s autonomy through its self-selection and demand-oriented work provisions.


NREGA: Reception and Perception NREGA has a positive impact on FLFP and wages. (Azam ,2012) 52.64% of the total of 305.71 Crore person days generated by the act were consumed by women in FY 2020-21. (Annual Report, 2021, MIRD) Studies in Andhra Pradesh find that greater participation of mothers in NREGA compared to fathers is associated with increased schooling of daughters, which creates compounding positive effects on FLFP rates. (Afridi et al., 2013) NREGA being a demand-based program was more accessible to women who were entering the labour force for the first time. Regularity and predictability of working hours and lesser chances of work conditions being exploitative were expected due to it being government work. A higher wage offered in NREGA works compared to prevailing wages adds additional incentive for female workers to work. Work being provided within 5kms of the household helped it to be considered socially acceptable and logistically feasible for women as they continued to bear the main responsibility of household work (Khera and Nayak, 2009). Another incentive for women workers was that each NREGA work site had to ensure that proper childcare was provided.

Figure 3.1 Percentage of Women Persondays out of Total (%) Person Days in a year under NREGA (Source: MoRD, GoI; Persondays: a unit of measurement, especially in accountancy, based on an ideal amount of work done by one person in one working day) Despite its gender-sensitive components, women participation in NREGA fell to a lowest in the last five years after a steady increase. While more research is needed to attribute this fall in participation to the global Covid-19 pandemic, a range of demotivating factors can also be posited to be the cause of this decline in FLFP.


Figure 3.2 Factors Facilitating Participation of Women in NREGA, Source: NIRD 2013


It can be inferred that motivating factors played a major role for participation of women in NREGA, whereas vulnerability factors compelled women to participate in the workforce. Though both vulnerability and motivating factors are responsible for participation of women in the workforce, FLFP is equally pulled down by de-motivating factors leading to overall low participation levels.

Filling Lacunae: Discrimination against single women in availing NREGA work, poor conditions of creche facilities, underrepresentation of women in the social audit process have all been documented in various field studies. (Sainath 2008, Frettsome and Gross 2011, Kheera and Nayak 2009) While most of these gaps were included in the operational guidelines of 2013 as additional clauses, the status and conditions of their implementation remains to be verified. The government’s mandate to switch to bank payments for direct wage payment to minimize corruption currently overlooks the lack of access and control that women assert on family bank accounts. Irregular wage payment and the low scale of employment generated - 30 days in the past 23 months per female worker also explain the declining levels of the female workforce.

The National Rural Livelihoods Mission (NRLM, 2012) was able to slow down the decline in the overall FLFP in treatment areas by almost 5.5%. 13.6% more women have been retained in the labour force in villages exposed to NRLM. (Kakkar, World Bank Publication, 2020) It can also be credited with bringing 7.7% women in the village back to work in just 2.5 years.


Figure 3.3 Changes in female WPR for full village - 2011 to 2016-17


Since 2012, NRLM has mobilized ~59 million women from poor rural households into Self-Help Groups (SHGs). These SHGs are then trained in basic accounting and financial management. They are exposed to regular savings, micro-credit, provided access to loans to finally gain access to diversified livelihoods including technical, microentrepreneurship and convergence with local government jobs and the private sector. The National Urban Livelihoods Mission (NULM, 2013) reserved a 30% quota for women under its employment schemes for the urban poor women, while also providing institutional credit and market opportunities to urban street vendors.

While these policies have successfully identified problem areas, most of the employment guarantee schemes do not lay out guidelines for on-ground implementation of their clauses, vis-a-vis promoting the acceptability of women employment in societies plagued with gender biases.


3.1.2. Gender Quotas


Operation Blackboard (1987) was one of the first schemes to provide at least 50% quota for female teachers (Fletcher et al, 2017). Even so, In the education sector, only ~42% of the teachers are women and this percentage decreases as the education institution level rises (AISHE-2018).


In Public Administration: Female Leadership raises aspirations and educational attainment for girls, creating a rolemodel effect. The 73rd and 74th Constitutional Amendment Acts in 1994 introduced reservation for women in elected bodies. A 1993 law mandated that one-third of seats on village councils (Gram Panchayats) be reserved for women. The electoral program quotas exerted effects on FLFP, female time use, and entrepreneurship, in addition to their direct participation in politics. Women in areas with female leaders were 39 to 52% more likely to start businesses than those in areas without leaders (Ghani et al., 2014). The gender gap in adolescent educational attainment was completely erased in villages with a reserved female head, while girls spent less time on household chores. Female participation in the MGNREGA increased following the election of female leaders. Female person-days worked in the program were higher by 6% in areas that were exposed to quotas (Bose and Das, 2014).

Despite a successful experiment with India's local governance and Panchayati raj system, the Women’s Reservation Bill (originally proposed in 1996) still has not been passed by the Lok Sabha after being reintroduced many times in the last two decades. It would reserve 33% of seats in India’s lower house of parliament for women - but has been awaiting passage in the Lok Sabha since 2010.

In PSUs: No reservations exist in this space despite the falling levels of female staff over the last few years. (10.2% (2017), 8.9% (2018) to 8.5% (2019), Department of Public Enterprises)

Central Armed Police Forces: There was a jump of 16.05 % in women in the police force in the year 2020. Even so, the percentage of Women Police is a mere 10.30% of the Actual Strength of the total Police force in the country. In 2015, a 33% reservation for women in the central armed police forces of India was announced. The reservations are going severely underutilised with targeted representation of women now raised to 15% in CRPF and CISF, and to 5% in BSF, ITBP and SSB to address the issue of underrepresentation of women.



3.2. Financial Inclusion & Women Entrepreneurs


Given greater propensity to hire more women, female entrepreneurs have a multiplier effect on overall job creation and female labour force participation. Only 14% out of the total 58.5 Million Businesses in India are run by women domiciled in the country (Sixth Economic Census, NSSO). India ranked 49th out of 58 countries judged on the basis of parity for women entrepreneurs in a study by Mastercard Index of Women Entrepreneurs (MIWE, 2020). The discouragingly low rank India received is because deterrents to women’s participation like fear of failure, lack of funding and lack of motivation continue to persist. Policies, thus, need to be designed keeping in mind the need for greater support for SMEs and a more positive socio-cultural mindset of its countrymen. Women-owned enterprises can generate over 50-60million direct jobs by 2030, making it an area policymakers should be looking to strengthen. (Bain&Company, 2019)


Figure 3.4 Women-owned enterprises can generate over 50-60 million direct jobs by 2030

The GoI has been seeking to address the challenge of access to finance and boosting female entrepreneurship through a spectrum of schemes in the last two decades. These include the Standup India scheme (2016), Pradhan Mantri MUDRA Yojana (PMMY, 2015), Pradhan Mantri Jan Dhan Yojana (PMJDY, 2014), Prime Minister’s Employment Generation Programme (PMEGP, 2008), Udhyam Shakti Portal for Women Entrepreneurs (2018) etc.

More than 240 million previously unbanked individuals, among whom about 47% are females, have gained access to bank accounts since the launch of the PMJDY 2014. Women’s’ businesses accounted for about 50% of the total amount lent under PMMY, and about 4/5th of the number of loans, in part reflecting the scheme's support to new business undertakings led by women. The Mudra scheme enables small new enterprises like beauty parlours, tailoring units etc.

It is estimated that the total financial requirement for women owned businesses in India in 2012 was $158 billion, but these firms accessed only around $42 billion from formal lenders, mainly from microfinance institutions. 90 % of India’s 90 million plus microfinance clients are women – but these small loans are in some cases not sufficient to help women grow their businesses.

Policies like National Policy for Women (2016), Udhyam Shakti Portal for Women Entrepreneurs (2018) include entrepreneurship development, training and skill upgradation, incubation facilities, training programs, providing mentor, market survey facility etc. Stand up India Scheme (2016) will facilitate two entrepreneurial projects on an average of one for each category (Women and SC/ST) of entrepreneurs per bank branch, with an objective of providing loans ranging from Rs.1 lakhs to Rs.1 Crore to at least one woman entrepreneur by one Bank each. In case of non-individual enterprises covered under the Scheme, 51% of the share capital and controlling stake should be that of the women. This scheme applies to greenfield enterprises which signifies first time ventures of the beneficiaries in the manufacturing, services, Agri-allied activities or the trading sector. Mahila Coir Yojana (1994) aims at empowerment of women artisans through the provision of spinning equipment at subsidised rates after appropriate skilling and training. It also has monthly stipends during training and innovations to increase women participation in the mostly male dominated manufacturing sector.

NABARD - SHG - Bank Linkage Programme (1992-93) and Rashtriya Mahila Kosh (RMK), also known as the National Credit Fund for Women (NCFW) (1993) were implemented to promote and finance Women Self Help Groups (WSHGs). To facilitate implementation of the Scheme, an exclusive fund viz. ‘Women SHG Development Fund’ was set up by Dept. of Financial Services, Ministry of Finance, Govt. of India in NABARD with a stated corpus of Rs. 500 Crore Grant support @ Rs 10,000/- per SHG to the Anchor agencies and the cost of publicity, training & other capacity building initiatives is met out of this fund.

Initiatives like Mahila E-Haat (2016) and the Women Entrepreneurship Platform (WEP, 2018) have also been launched to provide the requisite knowledge and ecosystem to women entrepreneurs. These include marketing support, free credit ratings and corporate partnerships.


3.3. Women Safety & Protective Legislation

3.3.1. Women Safety

Sexual Harassment of Women at Workplace (Prevention, Prohibition and Redressal) Act (POSH), 2013 was enacted with the objective to provide protection against sexual harassment of women at workplace and for the prevention and redressal of complaints of sexual harassment and for matter connected therewith or incidental thereto. The word “workplace” was defined to include any transportation service provided by the employer, protecting women against abuse in transit. A study found the majority (56%) of 655 districts surveyed did not respond to requests to provide data on the functioning of local committees to look into workplace sexual harassment and 31% of companies surveyed in 2015 were not compliant with the law. (Martha Farrell Foundation, 2018) Nearly 70% of the 539 complaints received under the Act, were pending three years after receiving them. (LokSabha,2020)

Domestic Workers (Registration, Social Security And Welfare) Act, 2008 while defining the hours of work for a domestic worker and minimum wages, specifically makes provisions for penalty in cases where a girl or woman domestic worker might be subjected to moral corruption or any manner of sexual exploitation.

Initiatives like the Working Women’s Hostels (1972) and the Mahila Police Volunteers Scheme exist to provide safe living spaces and supportive public-policy interfaces for women.

Efficient data collection into a centralized database needs to be done to first make up for the gross underreporting of the actual number of cases of harassment of women and then monitor the implementation of acts like POSH. Merely ‘prohibiting sexual harassment’ by law is not the completion of its process and these acts must include campaigns and workshops of gender sensitization. Redressal committees need to be formed in all workplaces and women need to be encouraged to register their complaints with the assurance that they’ll be properly investigated.


3.3.2. Protective Legislation


‘Protective Legislation’ in India jeopardizes women workers' right to equal opportunity and employment by unreasonably classifying them into a highly ‘vulnerable category’ not at par with men. Even though guidelines for safety for male and female workers are essential and must be evolved, a blanket ban on women’s engagement in certain processes is discriminatory and often has unintended consequences (Abraham et al, 2013). For instance, prohibition of women from working in underground mines keeps them away from the technical aspect of the mining industry. It pushes them to be employed as unorganized and often illegal workers with dismal conditions of work. Additionally, prohibiting women from working at night shifts has resulted in decrease in employment of women workers in these fields of work.

A 2018 press bulletin by the Ministry of Labour and Employment advised the amendment of Section 66 of the Factories Act relating to permission for employment of women for night work for a factory or group or class or description of factories with adequate safeguards for safety and provision of transportation till the doorstep of their residence.

In 2016, the central government passed the Model Shops and Establishment (Regulation of Employment and Conditions of Service) Act, permitting women to work during night shifts provided there is adequate provision of shelter, rest room, creches, ladies toilet, transportation and protection of dignity in shops and establishments employing ten or more workers (except manufacturing units).

Figure 3.5 Protective Legislation in India, Source: Abraham et al (2014), Women, Business and the Law, World Bank

Women in the Defence Forces: While there is no protective legislation that prevents women from serving in the Defence Forces of India, the legislation around recruitment was known to leave out women representation altogether. 5% reservation has now been provided to widows of defence personnel for short service Commission Women in the Indian Army. Fixed vacancies for women exist in the Defence Forces but women are then unable to compete with men based on merit and are allowed to apply to only those fixed vacancies. Women are not allowed to enter the armed forces after 10+2 and are required to at least complete their undergraduate to apply. Women continue to be protected from combat roles in the Infantry, Mechanised Infantry, Armoured Corps and the Artillery. There are no postings for women on ships and submarines in the Indian Navy.

In 2020, the Supreme Court of India made a landmark ruling that women officers of the Indian Army be granted Permanent Commission and command postings in all services other than combat. The Indian Army has the highest number of women serving as officers and is now the first force to allow females to join at the rank of Sepoys. In May of 2021, the first batch of 83 women soldiers was inducted into the Indian Army’s Corps of Military Police.


Creation of gender specific facilities to enable female postings, and gender sensitizations to enable good reception of women leading and working in predominantly male workforces are the need of the hour to encourage women to participate in the aforementioned fields of work.


3.4. Alleviating Time Poverty


The disproportionate allocation of domestic and care responsibilities prompts many women to experience time poverty which adversely affects their ability to participate in the labour market and work in the jobs that they may desire. This limits the occupations that allow time flexibility and management of care responsibilities to be the only viable ones for women.


Figure 3.6 Type of Work Women would Accept, by Age



3.4.1. Maternity


Most recently, the Government of India has taken a proactive stance for provision of child care for the organised sector women workers through the Maternity Benefit (Amendment) Act, 2017 which provides for enhancement in paid maternity leave from 12 weeks to 26 weeks and provisions for mandatory crèche facility in establishments having 50 or more employees. The minimum number of employees for the creche clause to apply warrants a revisit along with charting guidelines for locations, proximity to worksites which is currently absent from this act. It’s worrying how the act leaves out the women in the informal sector entirely and it remains to be seen if further amendments will include rural working mothers. While the Unorganised Workers Social Security Act, passed

in 2008, includes maternity benefits listed as one of the entitlements for the unorganised sector, no wage-linked scheme for this purpose has yet been notified by the government.

The only monetary entitlement currently available for all women is from the National Food Security Act (NFSA), that promises at least Rs 6,000 for all pregnant and lactating women. Janani Suraksha Yojana (JSY) is also a safe motherhood intervention under the National Health Mission. It is being implemented with the objective of reducing maternal and neonatal mortality by promoting institutional delivery among poor pregnant women. A noteworthy feature in the Plantations Labour Act, 1951 is the grant of 2 daily breaks to women resuming work after delivery for nursing their child till the child is 15 months old. These breaks are to be in addition to the regular rest intervals. (Section 32)

In 2017, The Menstruation Benefits Bill was introduced in the Lok Sabha to provide appropriate facilities to female employees during menstruation at workplace. It includes the right to menstrual leave including overtime allowance if a woman opts to work during her menstrual cycle, and the right to regulate working hours during menstruation.

By-products of gender sensitization are expected to follow if Bills like this are passed but what remains to be seen is if this increases gendered hiring discriminations associated with legislations around gender rights, contributing to a further decline in FLFP rates. For instance, one study describes how over 1000 MSME entrepreneurs interviewed, prefer to hire male employees since providing extended maternity leave and childcare facilities were expected to negatively impact their business and profitability (Joshi 2017). Efforts on the policy side to support employers on these inclusive measures could help in reversing this trend.



3.4.2. Childcare


Free childcare subsidies free up mothers time to enter the labour force and have had significant implications in impacting female employment. Additionally, these can also have positive spill over effects on the education of young girls. This is because a large part of sibling caregivers are girls who in the absence of childcare facilities for the mother, are left to take care of their younger siblings leaving them with little opportunity to attend school. As on 11.03.2020, only 6453 creches are functional across the country under the National Creche Scheme. An estimated 8,143 crèches have closed between 2013-14 and 2016-17, and the number of women and children benefiting from the scheme has been cut by 39% (from 474, 775 to 290,925). (Ministry of Women and Child Development: 2017) This worrying decline in Creche facilities and their funding needs to be investigated as it can have crippling effects on the lives of rural working mothers.


3.5. Wage Parity


As per ILO's flagship Global Wage Report 2018/196, which is published every two years, Indian women continue to be paid approximately 20% less than men. The Code of Wages 2019 replaces the following four laws: (i) the Payment of Wages Act, 1936, (ii) the Minimum Wages Act, 1948, (iii) the Payment of Bonus Act, 1965, and (iv) the Equal Remuneration Act, 1976.

The Code prohibits gender discrimination in matters related to wages and recruitment of employees for the same work or work of similar nature. Work of similar nature is defined as work for which the skill, effort, experience, and responsibility required are the same. Despite this, India scored a mere 25 points on a 100 points Pay Indicator scale in World Bank’s Women, Business and the Law report of 2021. While Indian laws mandate equal pay for equal work, it’s still far from guaranteeing equal pay for work of equal value which is what is required to address the years of social biases that led to gendered occupational segregation, relegating women to undervalued, low paid, oftentimes feminized work.


3.6. Skills & Education


Women who have participated in skills (vocational) training have higher levels of FLFP, regardless of educational levels - although the U-shaped relationship between education and FLFP persists.


Figure 3.7 Labour force participation by educational attainments of respondents based on participation in skills training.

The scope for improving skills and vocational training is significant. Many skills and vocational programs have been shown to be relatively ineffective (McKenzie, 2017; Blattman and Ralston., 2015); in India, some studies found that only 20% of trainees are employed one year after training in a major skills scheme in India (Artiz Prillaman et al., 2017).

National Policy for Women 2016 strengthens Anganwadi Centres to improve access to pre-primary education for girl children by involving community and sensitizing the parents. Gender friendly facilities include functional girls' toilets, and higher recruitment of women teachers for retention and increased enrolment of adolescent girls. Vocational skills as part of the secondary school curriculum. Mahila Samakhya aims to empower women by educating them, and also creates support groups on issues of social importance, such as domestic violence and alcoholism.

SarvaSiksha Abhiyan (SSA, 2000), has been one of the most ambitious programmes of the Government of India in the education sector. SSA was aimed at imparting quality education to girls and women. Under the Kasturba Gandhi Educational Plan (1997), educational institutions were set-up in the areas where the women’s literacy rate was very low.

National Education Policy (NEP, 2020) has introduced a Gender Inclusion Fund for targeting the development of the girl child. The GOI will constitute a “Gender Inclusion Fund” to provide quality and equitable education for all girls. The fund will focus on ensuring 100% enrolment of girls in schooling and a record participation rate in higher education, decrease gender gaps at all levels, practice gender equity and inclusion in society, and improve the leadership capacity of girls through positive civil dialogues. Funds will also enable States to support and scale effective community-based interventions that address local context-specific barriers to girls and transgender students.

Skill Acquisition and Knowledge Awareness for Livelihood Promotion (“SANKALP”) with loan assistance from the World Bank, targets Long Term Skill Development Training via Industrial Training Institutes (ITIs). There is nearly 97% increase in admissions in ITIs in 2018 as compared to 2014 to reach 173,105 women trainees from 87,799.

Pradhan Mantri Kaushal Vikas Yojana (PMKVY), Recognition of Prior Learning (RPL) scheme, Skills Strengthening for Industrial Value Enhancement (STRIVE) and Rural Self Employment Training Institutes are also major schemes to build and certify industry-relevant skills for women in India. The skill gap reports have identified sectors which are likely to have a higher percentage of women in the workforce. National Skill Development Policy uses innovative pedagogy, ensuring safe and gender sensitive training environments, employment of women trainers, equity in remuneration, and complaint redressal mechanism.


While these upskilling and educational policies address the supply of female labour force, it does not account for demand side factors that address first the recruitment of women, then their retention. Instances like that of the female garment workers in India having very high quit rates, losing almost 80 % of the workers in a study over two years raises questions about the quality of work and working conditions in these environments. (Adhvaryu, Kala, and Nyshadham,2016)


3.7. Women Empowerment


These policy reforms increased a woman’s autonomy, using autonomy as the channel through which the reform affected labour supply.


3.7.1. Transfer of Assets

Assets transfers in control trials showed an increase of work by 1hour per day in small enterprise activity in households. (Banerjee et al. 2011) Studies showed an increase in self-employment and quality of jobs among those women receiving transfers in Bangladesh, along with 1% increase in hours worked. (Bandiera et al. 2009)

The effects of transfer of assets through The Hindu Succession Act (HSA) 2005 on women’s labor force participation were examined and it was found that the HSA, which improved women’s ability to inherit property, increased their labor supply. Women exposed to the HSA were 6.8% more likely to work. It also led to a statistically significant increase of 6.6% in the probability that a woman has a say in household decisions. (Heath, Tan, 2014)


Figure 3.8: Empowerment index using women’s report of autonomy in decision-making on various expenditures

While the HSA has been associated with a range of other positive outcomes, including greater investment in girls’ education, delayed age of marriage, increased financial inclusion; other studies have uncovered some unintended consequences of this reform. These include parents circumventing the law so that daughters will not receive an inheritance, higher female infanticide and foeticide, and a higher suicide rate driven by a rise in marital conflicts. These unintended consequences point to the need for gender sensitisation of communities expected to uphold the provisions of the law.



3.7.2. Transportation/Mobility and FLFP


Women are more likely than men to lack access to motorized transport options (Salon and Gulyani 2010) and to spend more time traveling to paid work (Anand and Tiwari 2006). The effect of transportation may operate through increasing women’s access to nonfarm job opportunities, freeing up women’s time from family obligations, and changing gender attitudes among family members and local employers.

In communities with egalitarian gender norms (that is, where no one practices purdah or gunghat system), the odds of women’s nonfarm employment (versus farm work) increases by 78% when villages get connections by katcha roads, and it is more than doubled with connections by pucca roads. In addition, it has been found that improvement in road conditions tends to shrink the gender gap in non-agricultural employment by boosting the nonfarm employment of women more than that of men. Increased bus frequency between villages boosts the nonfarm employment of women in villages with egalitarian gender norms. In villages plagued by these practices, the increased frequency of buses had little effect on women’s employment. (Lei Lei et al., 2019)

Therefore, as one of the paths to economic growth, government investment in transportation has the potential to contribute to women’s autonomy and empowerment, making it a viable remedy to better India’s stagnant FLFP.


Figure 3.9: Changes in Women’s Employment with Changing Transport Infrastructure (Lei Lei et al., 2019)


3.7.3. Social Empowerment


Social Gender Bias: Despite its efforts in tackling social stigmas around women migrating for work and working odd hours, acts like the NREGA do little to address the hostility around women and their workforce participation itself. Sample surveys across six Indian States explained gender biases as ‘invisible’ barriers to women workforce participation as instances where women were turned away for being “too weak” for public works and the names of adult women being taken out of job cards. In the event of excess resources, women were the ones turned away and expected to make way for men who maintained their privilege in accessing these (relatively high paid) jobs. (Kheera and Nayak (2009)) Regressive gender norms prevent women from beginning or continuing their jobs, and from reaping the benefits of development in infrastructure that would help them access better, paid work.


4. Role of education and rising household wealth on Female Labour Force Participation in India


4.1. The Twin Challenge of Falling Female Labour Force Participation in India


There is a growing gap between male and female labour force participation rates (FLFP) in India. The FLFP in India has fallen to 25% (2018-19) from 30% (2011-12), implying an annual decrease in the proportion of the working-age population of females choosing to remain in the labour force.


Figure 1: Break-up of Male and Female Population across economic activity (2018-19)


The declining FLFP rates in India reflect both demand and supply side factors that make the determination of causation difficult [4.1].


On the supply side, Indian households often require that women prioritize housework and may even explicitly constrain work by married women [4.2, 4.3, 4.4]. Societal expectation of women’s role as caregivers and caretakers of the household often means that women who seek work encounter opposition from their peers and families, leading to lower participation. These societal views are frequently internalized by women and may therefore suppress labour supply even in the absence of such constraints. There is evidence that these norms per se have not significantly changed over the last two decades [4.5] and they are typically more binding among wealthier, upper caste households, suggesting that economic growth alone may not alter their influence. Low urban FLFP is consistent with this possibility (see graph below).


Figure 2: Female labour force participation rates across rural and urban areas


On the demand side, women face legal, normative, and economic constraints to work. Indian women are subject to laws governing when (i.e. which shifts) and in which industries they can work. These rules can disproportionately affect women even as the economy grows and their education levels improve: for example, female participation in export-oriented manufacturing jobs fell despite increased trade and reduced trade barriers during the 1990s, likely due to legal constraints on women’s working hours through the factory laws [4.6].


As long as there exist norms against women’s market engagement, we can expect to see gender-based discrimination in hiring, legal or otherwise. Also, gender wage gaps that cannot be explained by common sources of observable variation in wages shall also continue to persist. The lack of jobs that can absorb women transitioning out of agriculture further depresses demand for potential female labour [4.7].


Furthermore, high, sustained economic growth in India has not necessarily brought more jobs [4.8, 4.9, 4.10, 4.11]. Jobless growth in sectors that employ more women or seem more friendly to women necessarily limits growth in FLFP. In the 1980s, jobless growth was evident in manufacturing [4.8], and there is reason to believe women may have suffered from this relatively more acutely than males.


This section covers a deep dive into the role of education, female wages and household wealth on FLFP. There are four key hypothesis that shall be tested:


1. There is a U-shaped relationship between educational attainment and FLFP

2. Formal jobs have higher attractiveness for females than males

3. The wage elasticity of FLFP is higher than male labour force participation

4. Rising household income has a negative income effect on female labour supply


4.2. More Indian women are studying, but fewer are working


In economic theory, it is accepted that educational attainment drives Female Labour Force Participation rates (FLFP). However, the FLFP rates in India contradict this widely accepted theory.


Female literacy in India has increased from 36.9% (1992-93) to 68.4% (2015-16). The Net Enrolment Ratio (NER) for girls in higher secondary increased from 28% (2015-16) to 32% (2018-19). The percentage of educated females in the working-age population (15+ years) has also consistently increased across both rural and urban areas (see graph below).


Figure 4: Percentage of educated females (with general educational level of secondary & above) in the age group 15 years and above


Further, to supplement these findings, this is at a time when the sex ratio has also improved in India from 933 in 2001 to 943 in 2011 (Census of India). The fertility rate (parity) has declined from 4 children per woman in 1990 to 2.2 children per woman in 2019 (United Nations, 2020). Further, the median age of marriage for women has increased, although it continues to be low – 19.2 years in 2011 (up from 18.2 years in 2001) as compared to 23.5 years for men, according to 2011 Census data. Although all these trends, prima facie, strengthen the argument that more females must be entering and participating in the labour force, facts state otherwise.


The FLFP in India has been consistently falling from 43% in 2004-05 to 25% in 2018-19 despite an increase in educated, working age female population. Together, this means that India is not only finding it difficult to increase the proportion of females in the labour force but also witnessing a shrinking female labour force in absolute terms every year.



4.3. The market demand is not sufficient to absorb ‘Educated Females’ as they enter the working-age population


The issue of insufficient market demand for educated females has a clear rural-urban demarcation. While the Unemployment Rate (UR) among the rural male youth (persons of age 15-29 years) was 16.6% (2018-19), it was 13.8% among the rural female youth. On the other hand, for urban male youth, UR was 18.7% (2018-19) while it was 25.7% for urban female youth, indicating higher incidence of unemployment among young females in urban areas.


The net job creation in India over the past few years has been primarily in the informal sector, which is characterized by poor and unsafe working conditions, low wages and the lack of jobs and social security. Between 2004-05 and 2011-12, 14 million jobs were added in the economy, the bulk of which were in the informal sector [4.13]. Employment for women in the informal sector is a double-edged sword for not only are they paid less than the statutory minimum wages, but they are also paid less than their male counterparts. The persistence of stigmas against informal work has led to a lower level of participation rates among women with medium educational attainment.


On the other hand, the increase in white-collar jobs which are the only jobs likely to pull in highly qualified women in the labour market have not been able to keep pace with the increased supply of these women [4.14]. The share of white-collar services in urban employment has fallen from 19% in 1987 to 17% in 2009, while the proportion of graduates in the working age population has increased significantly from 11% to 21% [4.14].

Further, occupational gendering occurs on both sides of the labour market. There is a strong belief that when there is job scarcity, men have more right to opportunities than women. 84% of respondents in a Pew research study in India validate this belief.


Figure 5: Occupational Gendering in India

Consequently, there has been a crowding out of female labour participation because of oversupply of educated workers relative to the growth in jobs considered appropriate by them, thereby creating a ‘U-curve’ relationship between FLFP and general education levels for females in India.


Figure 6: Female Labour Force Participation Rate (%) in India across general educational levels (2018-19)

4.4. Role of Volunteer-Teaching and Mentorship Programs


Given the gap in educational attainment and female labour market, volunteer-teaching and mentorship programs can help improve the bargaining power for females in the labour market. To make an impact of FLFP though, this will require simultaneously creating sufficient jobs considered appropriate by females.


As more people work from home because of the ongoing pandemic, there is a growing need for mentor-led, career-focused partnerships by job-seekers (Springboard’s first mentorship survey). The current transition to remote work has significantly impacted career growth and development prospects for many in India. From leaders to job seekers, there is a pressing need to rethink how growth and development are perceived. Virtual mentoring programs can fill the major gaps in the current job market and help people across the world achieve their career goals.


The preliminary results of the survey revealed that not every professional could distinguish between teaching and mentoring. Mentoring and teaching are equally important but when it comes to professional learning and development, the process matters. So, should they go for a teacher, a mentor, or both? As per the survey, 62.7% of professionals prefer to take an upskilling program that gives them access to a mentor. The survey reveals that as many as 87.9% respondents think access to a seasoned mentor can profoundly boost their career success and trajectory while 79.4% feel that one of the best ways to transition to a position in a new industry is with the help of a mentor. Having access to an experienced mentor helps professionals identify and bridge their skill gaps and expedite knowledge acquisition to achieve their career goals. On being asked about challenges in one’s career growth, 41.9% of professionals chose ‘the need of a mentor to guide them’. The survey also revealed that 46.4% of respondents were unable to find a mentor that suited their needs.


In another study, it was found that although advocacy and mentorship exist for women throughout their careers, there are fewer opportunities for females in junior positions (Egon Zehnder, 2017). Interestingly, although access to mentorship in formal jobs is globally low for junior leaders, this proportion seems to be above average in India. 81% of employed women in India reported having access to senior leaders who also function as a mentor.



4.5. The nature of work and wage level is critical to improving female labour force participation


Increases in the rural and urban real wages in India post 2004-05 has largely boosted household incomes to the effect that the absolute number of poor fell by 138 million between 2004-05 and 2011-12 [4.15]. Rising household income increases the opportunity cost of domestic activities for women. Additionally, as the financial necessity of women to engage in outside work drops, most families are keen for women to stay at home as it is reflective of a rise in social status.


Figure 7: Scatter Plot of Female Wage Proportion to Household Expenditure

The existence of this income effect such that the rising income of a household serves to drastically lower the FLFP rate, is also a dominant supply side factor influencing the participation rate of women.


Key findings on the nature of employment and wage levels for females from the Annual Periodic Labour Force Survey 2018-19 have been summarized below:


● In rural areas, 71% of female workers were engaged in agricultural sector while in urban areas, ‘other services’ sector (other than ‘trade, hotel & restaurant’ and ‘transport, storage & communications’) shared the highest proportion of workers (46%), followed by ‘manufacturing’ (25%) and ‘trade, hotel and restaurant' (14%) (PLFS, 2018-19)


● In rural areas, among regular wage/salaried employees in current weekly status (CWS), earnings during the precedingcalendar month ranged from Rs 13,200 to Rs. 13,800 among males and it was around Rs. 8,000 to Rs. 9,400 among females (during July – September 2018, October-December 2018, January – March 2019 and April – June 2019)

● In urban areas, among regular wage/salaried employees in current weekly status (CWS), earnings during the preceding calendar month ranged from Rs. 18,900 to Rs. 19,500 among males and from Rs. 14,400 to Rs. 15,700 among females (during July – September 2018, October- December 2018, January – March 2019 and April – June 2019)


● Further, in rural areas, average wage earnings per day by casual labour engaged in works other than public works ranged between Rs. 277 to Rs. 297 among males and nearly Rs. 170 to Rs. 199 among females during the same period as above.

● In urban areas, average wage earnings per day by casual labour engaged in works other than public works ranged between Rs. 342 to Rs. 368 among males and nearly Rs. 205 to Rs. 244 among females during this period.


● In rural areas, average gross earnings during the last 30 days from self-employment work by the self-employed workers in CWS ranged between Rs. 9,100 to Rs. 9,600 among males which was nearly Rs. 3,800 to Rs. 4,400 among females during the same period.


● In urban areas, average gross earnings from self-employment work during the last 30 days ranged between Rs. 16,000 to Rs. 18,000 among males and it ranged between Rs. 6,200 to Rs. 6,900 among females during this period.


As a result, this significant wage differential in the labour market which exists at even high levels of education also impedes the participation of women.


The wage gap is higher in rural than urban areas. For graduates and above, it is as high as 31.3% in rural areas and 24.3% in urban areas. Thus, while competing for a small pool of formal sector jobs, instead of accepting poorly paid jobs, a significant proportion of educated women choose to remain out of the labour force.




5. Impact of Digital Trend, Remote Services and Work from Home


5.1. Definition and root cause of Gender Digital Divide


The gender digital divide can be defined as the gap that exists between those who have access to modern information and communication technology and those who do not and hence cannot benefit from the digital age. This gap exists between different genders due to lack of resources, socio-cultural norms, accessibility, education levels, etc.


There is a significant digital divide in the country, with rural women least likely to have internet access. In 2020, it was noted that only 14% of rural women in West Bengal had ever used the internet as compared to 38% of rural men. In urban areas, the worst performing state was Andhra Pradesh where only 33% of women had ever used the internet vs 65% of men.

In 2019, it was noted that the average internet penetration for India was 38%, with Delhi performing the best at 69% and Odisha performing the worst at 25% (Statista – 2019).



In 2017, 1/5th of women in India were identified to believe that the internet was not appropriate for them (OECD-2018). In 2012, 8% of women did not use the internet due to lack of acceptance from family members (Dalberg & Intel – 2012). It was noted that active female internet users were 3 times more likely to have supportive family members. Much of the opposition was for safety reasons and socio-cultural norms.


Much of India heavily relies on informal networks for filling vacancies and getting employment. This has not changed despite increased worker mobility or with business disruptions. Having access to the internet and ongoing digital transformation is expected to create comprehensive labour platforms and therefore better labour force participation can be expected if internet access becomes universal. Increased internet penetration helps women search and identify potential job opportunities, upskill themselves and provides access to online marketplaces.


This is evidenced by the strong correlation between internet usage by women and female labour force participation in urban areas in India. The best performing state was Himachal Pradesh where ~79% of women have used the internet and the FLFP corresponded to ~28%. On the other hand, Bihar was the worst performer, where only ~38% of women had ever used the internet and the FLFP was at ~6%.


Figure 2: Correlation between FLFP and access to Internet (Urban)

The correlation between education level of more than 10 years and internet usage was higher in urban areas, where Sikkim performed the best where ~90% of women had used the internet and ~60% had completed 10 years of education. The worst performing state was Tripura where ~36% of women had completed 10 years of schooling and ~36% of women had ever used the internet.


In urban areas, Goa performed the best, where ~69% of women had more than 10 years of education and ~68% of women had used the internet at least once. The worst performer was Andhra Pradesh where ~34% of women had this educational requirement and only ~14% of women had used the internet at least once. But this was not consistently noted in other states as one would expect. For example, Sikkim, wherein women who had this educational requirement was ~41% but ~68% had at least used the internet once which does not support the universal theory that higher education leads to higher internet usage.


Figure 4: Correlation between education level and internet usage (Rural)


Figure 5: Correlation between education level and internet usage (Urban)


5.2. Impact of Digital transformation on Female Labour Force Participation


Digital transformation is expected to strengthen women’s position in the labour market globally, but in India this does not seem to be the case. As of 2020, 67% of women in India work in sectors which can be highly automated (Agriculture - 55%, Manufacturing – 12%).

The main obstacle to automation could be the low wage rates in India, but this can only delay the inevitable.


Accommodation and food services industry, manufacturing, agriculture, transportation, and retail trade are the industries with more than 50% automation possibility for each of them.

Figure 6: FLFP per sector

FLFP has seen a consistent shift across the last 25 years from agriculture sector to manufacturing, construction, and services sector (5.1). The services sector includes domestic work, healthcare, etc. This shift is common for both rural and urban areas, but the trend has been at a much faster pace in the urban areas.




The susceptibility to automation for a sector depends on the predictability of the work performed in that sector. India is one of 4 countries where 2/3 of the employees work in activities which are automatable by adopting current technology (McKinsey – 2017).

It is also expected that many emerging economies could experience stronger growth in demand for higher-wage jobs, but these are in field requiring higher education and digital skills. Long-established barriers such as unpaid care, physical safety, access to digital technology and participation in STEM fields will make it harder for women to make transitions in this period (McKinsey – 2019).


Additionally, in emerging economies, having secondary education, undergraduate education or advanced degrees can highly improve chances in securing employment in the age of automation (MGI – 2019).


Currently in India, only 47% of women have completed 10 years of education with the rural average at ~37% and the urban average at ~59%. The rural average is more worrying as ~73% of women are employed in agriculture which is a highly automatable sector.


In the below figure, the state-wise % of women with more than 10 years of education is shown where Kerala and Goa are the best performing states with ~70% of women in both rural and urban areas having completed 10 years of education.


The sectors which are least susceptible to automation are jobs which require skills such as technological, social, and emotional skills and the need for these are expected to rise, and the demand for physical and manual skills will fall. The major sectors which are least automatable include education, management, professional services, and healthcare to a certain extent. Currently in the education sector in India, only ~42% of the teachers are women and this percentage reduces as the education institution level rises (AISHE-2018).


In developing economies, like India, the significant FLFP working in the agricultural sector with limited education may face difficulty obtaining employment in other sectors with less automation susceptibility. Women who choose to remain in their current jobs, would need to learn how to work alongside automation to be able to keep their jobs (McKinsey-2019).


Long-established barriers faced by women make it harder to make transitions in the age of digital transformation. They have less time to reskill themselves or search for employment in other sectors because they spend much more time than men on unpaid care work; are less mobile due to physical safety, infrastructure, and legal challenges; and digital divide and participation in STEM fields than men.


If women take advantage of transition opportunities, they could maintain their current share of employment; if they cannot, gender inequality in employment could worsen.


5.3. Role of digital solutions in female labour force participation


Digital solutions such as e-commerce websites have provided women access to the marketplace which have had a positive impact on female labour force participation (IndiaSpend – 2020). Additionally, gig economy jobs such as UrbanCompany also provide women in urban areas employment opportunities which are flexible in terms of work hours.

Many women who opted for gig jobs were able to get 3 times their earlier income. Certain aspects did not change with the movement to a gig economy. This included gender wage gap and lack of social security. Many women working for Uber, UrbanClap, etc can only work during the daytime or in certain areas due to safety issues which leads to lower income than men.


Additionally, mobile apps like Big Basket, Grofers, etc have also eased the burden of women participating in the labour force, by reducing time spent on caregiver activities such as buying groceries typically expected of women. Food delivery applications also reduce time spent on cooking, and the option of peeled, chopped vegetables from grocery applications also reduce time spent on cooking, especially during the pandemic.


Social media applications have been a surprising contender in providing employment. These applications such as Tik Tok, ShareChat and Instagram have been a boon for women outside the big cities. Young women in rural India with over a million followers were able to get ~4000 INR from each video they posted.


Recent initiatives such as Amazon Saheli where Amazon supports women sellers on their marketplace by providing them subsidized referral fee, personalized training, account management support, imaging and cataloguing, increased visibility, etc. They have also designed a separate store to showcase the products from these women entrepreneurs. Currently, they have over 80,000 women artisans under this programme.


Other solutions include job platforms such as QuickrJobs (Earlier Babajobs) which is platform which connect blue collar workers to potential employers. Currently there are 2000+ job openings for women specifically (McKinsey – 2019), but due to the digital divide, the awareness of this platform would be low.


6. Status of Female Unpaid Caretaker in India

6.1. Defining Unpaid Caretaker


Unpaid caretaker as an umbrella term covers several types of task which can be classified under four major dimensions (ICRW, 2019)


● Uncompensated merchandizing and livelihood supporting activities such as voluntary work done by other family members in farm or enterprises.


● Activities are done for one’s self-consumption such as milling, weaving and other refinements of agricultural products.


● Accumulating free goods like water, fuel and fodder for manufacturing and consumption.


● Work is undertaken for household care and nurturance.


6.2. Unpaid Women Workforce in India: A perspective


A survey report published by the Ministry of Statistics & Program implementation in 2019 naming Time use in India reflected the concept of ‘time poverty among women in terms of paid work. Moreover, in India men devote 80% of their working hours to paid work while women commit 84% of their time to unpaid work. The percentage of Indian women who work to get paid is significantly lower than that of their male counterparts.


Only 21.8% of women between the ages of 15 and 59 worked for a living, compared to approximately 70.9% of men. However, when both paid and unpaid employment is considered, women's participation rises to 85%, while men reported at 73%.


As per the World Bank, women's participation in the labour force in India has decreased by approximately 30% in the past 20 years. Yemen, Iraq, Jordan, Syria, Algeria, Iran, and the West Bank and Gaza Strip are the only countries with the lowest female labour force participation.


In 2019, the average Indian woman spent 243 minutes per day on domestic tasks and household duties, about ten times the 25 minutes spent by the average Indian man. In a typical day for an Indian woman vs. a man, the following graph compares the distribution of work hours across numerous activities.


While uncompensated private tasks by women account for almost 13% of the global economy, it is estimated that unpaid domestic labour by women accounts for approximately 40% of India's current GDP. This, in turn, shows the amount to which their efforts go unnoticed.



6.3. Genesis and Status of Unpaid Female Caretakers in India: Identifying Drivers


Unpaid labour by women is an important gear in the wheel since it contributes to the overall well-being of households and the economy. While this is recognised, there are few solid policy measures in place to protect their interests.


The situation in India, in particular, is much grimmer when it comes to women's unpaid labour. While societal factors such as sexism encourage unpaid work, overall female labour force participation is shockingly low. From a standpoint, fewer than 25% of the female population works as part of a paid workforce, with 70% of those working in agrarian and allied industries, where recompense and recognition for their labour are rudimentary.


However, multiple reasons contribute to the present situation including the expected marriage age and responsibility of bringing offspring hence burdening with household chores. For example, a significant rise of 6% was observed among women population (aged 25-34) engrossed as a caregiver as per the data collected from 1993-94 to 2011-12.


6.3.1. Caste

While determining the gendered division of time and labour in Indian culture, factors such as interconnections of caste and geography can’t be ignored. In a survey where individuals were categorized into Scheduled Caste (SC), Scheduled Tribe (ST), Other Backward Castes (OBC), and Other Castes (OC) where OC symbolizes upper-caste found that men and women from upper caste got least involved in unpaid tasks and paid work, respectively. The next graphs highlight the stark discrepancies even more.


6.3.2. Geographical Divide: Urban vs Rural; Northern vs the Southern States


Geographic differences in women's time allocation to paid and unpaid employment also exist. Indian women spend over 390 minutes in unpaid tasks in rural areas and a bit less in metropolitan areas (360 minutes). Males in urban regions spend 31 minutes less per day on unpaid labour than men in rural areas. A comparison between northern and southern areas showed women spending less time doing unpaid work in the former and males are less likely to help with domestic work in the latter. Haryana is the most unequal of the Indian states in the sense that men aged 15 to 59 doing only 15 minutes of unpaid housework each day compared to 269 minutes for women of the same age.



The proportion of Women Performing Unaccounted Economic Activities:


6.3.3. Psychosocial Factors:


1. Patriarchy


In India, social standards dictate that women perform unpaid labour, and deviating from this standard can result in domestic violence, among other things. According to OXFAM India's 2019 home care survey, 33% of respondents believed it was legitimate to beat a woman for not looking after her children or failing to attend to a dependent or unwell adult member of the household. 68% of study respondents said women should be harshly chastised and 41.2% believed they should be punished for failing to cook supper for the family's men.


2. Gender Polarisation


This is due to the belief that women are made for household responsibilities. Surprisingly, the urban-rural gap does not appear to be a deterrent to this viewpoint, as over half of the men polled in Mumbai's Tier 1 city agreed (Mint, 2018). This can be described as a gender polarisation of expected work outcomes from a subject gender, resulting in gender-based bifurcation of work positions (6.2, 6.3). Women's work has been devalued, and their exclusion has reinforced the gendered split of paid and unpaid labour, leaving women without pay and little negotiating leverage in the home, and allowing the vicious circle to continue where men, economy and nation grow at their rate.




7. Policy Recommendations

1. Gender Sensitization for Effective Implementation (In reference to Section 3.7.3, ‘Social Empowerment’): Gender sensitization drives and induction of gender-sensitive officials are vital to effective and efficient implementation of gendered clauses, to address and promote the acceptability of female employment.

2. Intercepting Discriminatory social organizations: Carefully juggling with accustomed gender compartmentalization and social roles can bring equilibrium in caring responsibilities among men and women and thus ‘de-feminizing’ the caregiving jobs. To reinforce male involvement in home-based care assistance for people living with AIDS in a rural area, Zimbabwe released a project “Africa’s Male Empowerment project” to interchange the behavioural trends and dealing with the rudeminting gender norms.


3. Incentives to Employers (In reference to Section 3.4.1, ‘Maternity’): Wage subsidies could be included in policies to prevent gender inequalities in hiring practices. Companies in the private sector need to be incentivized to hire women and the government can support these companies by bearing the costs of gender-sensitive schemes in the initial years.

4. Financial Inclusion (In reference to Section 3.2, ‘Financial Inclusion & Women Entrepreneurs’): Policies enabling and facilitating financial inclusion need to address hindrances to inheriting property and women’s diminished access to formal credit due to lack of these collaterals.


5. Economic Development Policies and Time Saving Technology (In reference to Section 3.7.2, ‘Transportation/Mobility and FLFP’): The role of economic development policies, such as transportation infrastructure investment and e-commerce, in shaping women’s labor market activities require more research and attention.


The two factors which have significantly saved women’s time are electrification and better water supply. For example: In Africa with the introduction of rural electrification, there was a significant decrease in the hours women spent on household chores, thereby increasing the female participation in labour by 10% (7.2). Similarly In Pakistan localities that were closer to a water body reported less time in house-related tasks and better female employment (7.1).


6. Education (In reference to Section 3.6, ‘Skills and Education): Intergenerational transmission of gender attitudes could be reduced by fostering inclusive learning in schools and facilitating behavioural changes to bring out generations of people supportive and accepting of female employment.


7. Quality Work (In reference to Section 3.6, ‘Skills and Education): Poor retention of women in the workforce needs to be addressed by ensuring the quality of work created through public employment schemes, including the working hours and the facilities promised on worksites like creches, sanitation etc. Conversely, there is also an absence of re-entry schemes for women who have had to exit the labour force for various reasons.


8. Enhanced public services and childcare assistance: Easy access to public services, childcare and geriatrics care facilities further foster work-life balance. In India, an NGO named Mobile Creches provides childcare assistance for women who are working in construction sites to become a helping hand for the employed mothers. Other alternatives done by the Kenyan government include expanding pre-school education to four to five-year-olds which subsequently led to an increase in female labour participation might also be implemented. Other options such as increasing school time or stretching pre-school hours might also help.


9. Fostering care lens among several domains of public policy: Introducing specific fiscal policies where especially women as second earners should not be heavily taxed thereby increasing female labour participation. In Japan, there was a significant increase of 13% in female participation as labour when in between spouses high tax incentives were allocated to share market tasks (in a way highlighting unpaid care work).


10. Data Allowances (In reference to Section 5.1, Definition and root cause of Gender Digital Divide): Policy makers should consider providing data allowance coupons for women, similar to universal food rations which would enable them to search for jobs, upskill themselves and raise awareness about various social issues impacting them.

11. Addressing Information Asymmetries (In reference to Section 5.1, Definition and root cause of Gender Digital Divide): Campaigns to raise awareness about the internet and workshops to help women to learn how to access the internet and use a mobile phone are essential to employment in the digital age. Campaigns should be centered around not just the importance of the internet, but also to remove the taboo around women’s usage of the internet and its appropriateness. Utilising SHGs to share information around jobs and welfare schemes can be inducted into policies.


12. Enabling Access to the Internet (In reference to Section 5.2, Impact of Digital transformation on Female Labour Force Participation): Policy makers and businesses need to intervene to help women overcome barriers such as the digital divide, access to reskilling opportunities, mobility challenges, etc. High priorities should be for more investment in training and transitional support; addressing stereotypes about occupations; boosting women’s access to mobile internet and digital skills in emerging economies; and supporting women in STEM professions and entrepreneurship.


13. Upskilling (In reference to Section 5.2, Impact of Digital transformation on Female Labour Force Participation): NGOs and businesses should consider employing a Hire-Train-Deploy model where over the course of a few months, women participants would be trained in valuable IT skills such as Java, testing, basic MS office tools which are in-demand skills and help them to get employment.

14. Online Talent Marketplaces (In reference to Section 5.3 Role of digital solutions in female labour force participation): Creation of a comprehensive platform of labour market information is essential to increasing FLFP, especially in the digital age. This would help measure and match demand and supply for skills and by geography. Based on benchmarks from global experience, it is estimated that large online talent marketplaces could help 20 million to 28 million people secure work that they otherwise would not have found (McKinsey – 2019).


Years of systemic and regressive norms have stymied women’s labour force participation. Combined with lack of economic and infrastructure development, access to contemporary digital skills, and time poverty, women’s supply into the labour force has only decreased further over the years. Wage gaps, working hours, harassment at work and apprehensive employers have hindered recruitment and demand of jobs employing women. Only a smarter policy response that creates social, market and digital reforms can be expected to have any beneficial impact on gender equality, thereby bolstering India’s FLFP.



If you are interested in applying to GGI's Impact Fellowship, you can access our application link here.



 

Meet The Thought Leaders


Shatakshi Sharma has been a management consultant with BCG and is Co- Founder of Global Governance Initiative with national facilitation of award- Economic Times The Most Promising Women Leader Award, 2021 and Linkedin Top Voice, 2021.

Prior to graduate school at ISB, she was Strategic Advisor with the Government of India where she drove good governance initiatives. She was also felicitated with a National Young Achiever Award for Nation Building. She is a part time blogger on her famous series-MBA in 2 minutes.


Naman Shrivastava is the Co-Founder of Global Governance Initiative. He has previously worked as a Strategy Consultant in the Government of India and is working at the United Nations - Office of Internal Oversight Services. Naman is also a recipient of the prestigious Harry Ratliffe Memorial Prize - awarded by the Fletcher Alumni of Color Executive Board. He has been part of speaking engagements at International forums such as the World Economic Forum, UN South-South Cooperation etc. His experience has been at the intersection of Management Consulting, Political Consulting, and Social entrepreneurship


Karan David is a mentor at GGI and a management consultant at Bain & Company's India office. He graduated from St. Stephen's College, Delhi with Honours in Economics. Outside of work, KD is a travel enthusiast, a connoisseur of good food and enjoys listening to music and playing video games in his free time.





Meet The Authors (GGI Fellows)


Swasti is a Senior Consultant with Deloitte and holds a Master’s in Public Policy. She is an engineer-turned policy practitioner with experience in impact evaluation studies, policy advisory,

government affairs and youth diplomacy. She has represented India at the 1st BRICS Youth Summit and is passionate about solving issues around just transition.


Melissa is a Lead Internal Auditor at Societe Generale in Bangalore. She has 3 years of experience which includes auditing various fields such as capital markets, loan financing,

accounting and regulatory compliance. She has volunteered with various NGOs and awareness campaigns for various social issues.


Arpita is an Associate Consultant with Deloitte, having worked in Financial & Cyber Risk Advisory for global clients. She’s the host and producer of ‘The Saltwater Tree Party’; a podcast

on wetlands conservation for climate change mitigation. She also volunteers with WWF-India for biodiversity conservation in her free time.



Priyal is a Chartered Accountant by qualification currently working in the consulting domain. She is also an ex-member of the Indian rifle shooting team and the co-founder of a sports-based NGO in India.





Abhinav is a Chemical Engineer, pursuing a Master’s in Engineering Management. He has worked in large and mid-sized petrochemical plants, as well as a management consulting startup. He has also served as treasurer and advisor to an NGO based in India.




Ronak is a researcher at McKinsey. He holds a doctorate in organizational behavior and masters in English Literature. He is an internationally published author with his case studies

currently taught at the likes of Oxford University, Goldman Sachs and IIM-A. He has been recognized by the ruling government for campaigning on social impact issues such as menstrual hygiene.


If you are interested in applying to GGI's Impact Fellowship, you can access our application link here.


 

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