How COVID-19 Deepened the Gender Fault Lines in India's Labour Markets

India has witnessed low levels of women’s labour force participation over the last four decades, with gaps of nearly 40 percentage points between the proportion of men and women in the labour force. Recent high-frequency data shows that COVID-19-induced lockdowns have had a disproportionate impact on women’s employment. Women bore the immediate impact of lockdowns, with 37.1% losing jobs (versus 27.7% men) in April 2020 and forming 73% of job losses in April 2021. Employment recovery has been slower for women. Prevailing sociocultural factors such as the increased burden of unpaid domestic work, gender digital divides, mobility restrictions, and the lack of institutional support at workplaces are discouraging women’s return to work. Even in January 2022, women’s labour force is 9.4% lower than January 2020 versus 1.6% for men. In this scenario, governments can support through gender-sensitive job-creation plans to expand women’s employment in the public and micro, small and medium enterprise sectors, and incentivise women’s entrepreneurship.

Since independence in 1947, India has rapidly progressed across social and economic fronts, and has continued to remain an economic powerhouse globally, even in light of COVID-19. However, the Indian economy is dealing with a unique conundrum, such that despite gains in female education and falling fertility rates, even today, only about a fourth of Indian women participate in the workforce. COVID-19 has only worsened this situation, displacing millions of women from the labour force itself.

This paper aims to highlight the disproportionate impact of the COVID-19 pandemic and associated lockdowns on women’s employment in 2020 and 2021. The paper with an analysis of time series data (at the all-India level) over the last five decades (1970-2019) to capture long-term trends in labour market outcomes for women. This data was sourced from the Periodic Labour Force Surveys conducted by the National Sample Survey Organisation, published by the Ministry of Statistics, Programming and Implementation, Government of India. Following this, high-frequency data from the Centre for Monitoring Indian Economy (CMIE) is analysed to gauge the impact of COVID-19.

Long-term Trends in Female Labour Force and Work Force Participation

The difference between the proportion of men and women in the labour force has remained at ~40 percentage points over the last four decades. India’s female labour force participation rate (FLFPR) for those in the working age (15 years and above) declined steadily from 47.1% in 1987-88 to a dismal 23.3% in 2017-18, the nadir in the history of independent India (NSSO 1987, 2018). In the last two surveys, the FLFPR has improved slightly, rising to 24.5% in 2018-19 and further to 30.0% in 2019-20.

The exodus of rural women from the labour force has been a key driver behind falling FLFPR, especially since 2004. The rural FLFPR has nearly halved between 1987-88 to 2017-18 when it fell from 53.7% to 24.6%, later increasing by 8.4% to 33% in 2019–20. The urban FLFPR fell from 26.1% in 1987-88 to 19.4% in 2009-10. It has remained constant at 20.5% since 2011-12, increasing marginally to 23.3% in 2019-20 (Figure 1).

Figure 1: Rural and Urban LFPR (15 years and above) (1987–2019) (NSSO)

Moreover, it was observed that massive declines in female workforce participation rates (FWPRs) over the last four decades have not translated into higher unemployment rates (URs), but rather into lower FLFPRs. Between 1987-88 and 2019-20, the rural FWPR fell from 52.8% to 32.2%, whereas the urban FWPR fell from 25.1% to 21.3% (Figure 2). On the other hand, while URs for urban women rose from 5.2% in 1987-88 to 10.8% in 2017-18 but then saw a marginal decrease to 8.9% in 2019-20, for rural women, the increase was marginal, from 1.7% to 2.6% for rural women in this period (Figure 3). This is indicative of a pattern where women, especially rural women, were exiting the labour force rather than continuing their job search upon losing employment.

Figure 2: Rural and Urban WPR (15 years and above) (1987–2019) (NSSO)


Figure 3: Rural and Urban UR (1987–2019) (NSSO)

Over the last four decades, there was an increase in the proportion of employed women working as salaried or regular workers in urban areas. The proportion of women in salaried work almost doubled from 25.8% to 54.2% between 1983-84 and 2019-20 in urban areas. This is in stark contrast to the mere 4 percentage point increase for urban men from 43.7% in 1983-84 to 47.2% in 2019-20. This was also accompanied by a fall in the proportion urban women engaged in casual labour, from 28.4% in 1983-84 to 11.1% in 2019-20 (NSSO 1983, 2020).


  1. Impact of COVID-19 on women’s work

The disproportionate impact of COVID-19 on women’s economic participation manifested in three ways during the pandemic years (2020 and 2021). First, women bore the immediate impact in all three waves of COVID-19 and the subsequent lockdowns. Second, women’s employment was slower to recover, as compared to men, with employment recovery for urban women being the slowest. And third, COVID-19 hampered income growth for women-led enterprises, signalling a long-term impact.

    1. Trends in employment during the first COVID-19 wave (March 2020–June 2020)

A nation-wide lockdown was imposed in March 2020 to prevent the spread of COVID-19. Following the lockdown, about 113.6 million workers lost their jobs between March and April 2020, out of which 15.4 million were women. While the absolute fall in male employment was far greater, the proportionate fall for women was higher since 37.1% of women lost their jobs compared to 27.7% of men (CMIE 2020).

Rural women were the worst hit by the first wave. Employed rural women experienced a steep initial dip, from 29.8 million in March 2020 to 17.8 million in April 2020, that is, by 40.2% versus 25.5% for rural men. On the other hand, urban female employment fell from 11.8 million in March 2020 to 8.3 million in April 2020, that is, by 29.2%, versus 32.4% for men (Figure 4).

Figure 4: Number of Employed Males and Females during First Wave of COVID-19 (2019-2020) (CMIE)

Trends in Employment during the Second COVID-19 Wave (April 2021–June 2021)

As trade and mobility restrictions eased, total employment almost recovered to March 2020 levels by November 2020, 394.1 million (November) versus 395.8 million (March). However, the gender distribution changed, as 3.1 million fewer women were in employment, but 1.4 million additional men found employment.

Nevertheless, employment recovery continued so that by March 2021, 356.2 million men and 41.9 million women were employed, exceeding March 2020 levels (354.2 million and 41.6 million, respectively) slightly. And then the second, more deadly wave of COVID-19 hit the country.

Unlike the first wave, in the second wave, women bore not only a higher proportion, but also higher number of absolute job losses. About 7.4 million persons suffered job losses in April 2021, 5.4 million women (12.9% of female labour force), versus 1.9 million men (0.5% of male labor force), that is, women suffered 73% of job losses (CMIE 2021).

Moreover, there were significant differences in the impacts on urban and rural female employment. In April 2021, the number of employed urban women grew from 9.3 million (in March 2021) to 9.5 million. On the other hand, 5.7 million rural women lost their jobs in April 2021 alone, thus resulting in a net job loss of 5.4 million for women (Figure 5).

Figure 5: Number of Employed Males and Females during Second Wave of COVID-19 (2020-2021) (CMIE)

Trends in Employment Recovery and Migration in the First Two Waves

With gradual relaxations from June 2020, employment numbers started recovering to pre-pandemic levels. Urban women had the slowest recovery among all categories, with a compounded average monthly recovery rate (CAMRR) of (-)2.1% between March 2020 and March 2021, versus (-)0.03% for urban men. On the other hand, though rural women’s employment recovered unevenly, they registered the highest job growth, with CAMRR of 0.81% versus 0.09% for rural men (Figure 6).

As the effects of the second wave subsided, employment levels for all categories saw a sharp recovery by December 2021, with job growth among rural women being the highest at 3.82% CAMRR. Even though urban women saw recovery in employment, their CAMRR remained the lowest among all categories at 0.83% even in December 2021 (Figure 6).

Figure 6: Recovery Rates of Employment (March 2020-March 2021, March 2020-December 2021) (CMIE)
Note: Recovery rate is calculated as the compounded average change in number of persons employed between March 2020 to March 2021, and March 2020 to December 2021.

Driving this growth in rural women’s jobs in 2020-21 were the job losses faced by urban women, concentrated in sectors deeply impacted by the COVID-19 pandemic, who were pushed back into rural work. Between March 2020 and 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 among men, with male rural employment increasing by 0.8%, and urban employment falling by 0.3% (Figure 7).

Figure 7: Change in Urban and Rural Employment (March 2020-March 2021)


Trends in Employment during the Third COVID-19 Wave (November 2021-January 2022)

On the other hand, the third wave, which hit in December 2021 disproportionately impacted men in January 2022, primarily in rural areas. While the total number of employed rural men fell by 5.3 million, about 0.9 million urban men lost jobs. On the other hand, rural women’s employment increased by 2.4 million, and urban women’s by 0.5 million (Figure 8). 

Figure 8: Number of Employed Males and Females during Third Wave of COVID-19 (2020-2021) (CMIE)

Overall, three waves of the pandemic and several state-wise lockdowns later, gender gaps in employment levels continue even in January 2022. In January 2022, 3.4% fewer women are in employment, and the size of women’s labour force has contracted by 9.4% versus January 2020. On the other hand, the size of the male workforce is 0.4% lower, and labour force is 1.6% lower. In addition, 79% of unemployed men were actively looking for jobs versus only 36% of unemployed women, suggesting a long-term discouragement among unemployed women (CMIE 2020-2022).

Sociocultural Factors driving the Trends Women’s Employment during COVID-19

Between August 2020 and December 2021, Nikore Associates (a youth-led economics research group) undertook three rounds of consultations with about 70 women-led community organisations, self-help groups (SHGs), corporates, and academic experts with the objective of understanding the impact of COVID-19 on women’s work. Based on these consultations, a number of sociocultural factors driving these trends in women’s work were identified and are discussed below.

Increase in burden of unpaid work. Prevailing cultural norms expect women to prioritise unpaid domestic work, sacrificing paid work in favour of care responsibilities in the home. Pre-COVID-19, working-age women spent 5.6 hours on unpaid work versus 40 minutes for men (Time Use Survey, 2019). Our consultations revealed that regardless of geography or occupation, women consistently reported an increase in domestic workload since the start of the pandemic. This was largely driven by school closures, closures of childcare centres, increase in elderly care, and presence of husbands/male relatives for longer periods at home. Further, several stakeholders reported that men were unwilling to contribute to housework, despite being at home during lockdowns, especially in rural areas.

Gender Digital Divide

India suffers from pervasive gender-based digital divides, with gender gaps of up to 15% in mobile phone ownership and 20% in internet usage in 2020 (GSMA 2020). During stakeholder consultations, multiple female entrepreneurs cited the inability to pivot to digital marketing or start online businesses due to lack of mobile ownership or digital illiteracy. Continuing with pre-COVID-19 biases, adolescent girls were denied access to smartphones by their families, disrupting online schooling and/or skill training.

Mobility Restrictions

Even before COVID-19, only 54% of women were allowed to go a nearby market alone, and only 48% could visit places outside their village or community by themselves (National Family and Health Survey 2015-16). Heightened mobility restrictions and disruption of public transport services lowered women’s access to workplaces, hampering their ability to participate in the labour force and earn livelihoods. Several stakeholders shared that they required strong reasons to leave the home, inhibiting their ability to work.

Lack of Institutional Support in the Work Ecosystem

Women working in both formal and informal set-ups faced worsening working conditions during COVID-19, prompting them to opt for changes in their job, or even exiting the labour force altogether.

Stakeholders noted that women in the corporate sector faced multiple challenges with the “work-from-home (WFH)” model, despite its inherent flexibility. Women felt greater pressure to perform and faced considerable microaggressions from managers, resulting in long hours and mental distress. Several women also shared that their productivity fell due to the lack of private workspaces within the home. Moreover, despite belonging to multiple earner families, women took up a much greater proportion of unpaid domestic, child and elderly care work. For instance, a survey from Deloitte India showed that the percentage of women rating their job satisfaction as good or extremely good fell from 69% to 28% in 2020.

Moreover, informal women workers—be it street vendors, domestic workers, or factory workers—experienced extreme vulnerability in light of falling household incomes. Stakeholder consultations corroborated that falling household incomes were pushing women towards marginalised jobs with extremely poor working conditions. For instance, a woman street vendor selling flowers outside  Tirupati temple shared that her income dried up almost entirely during the peak of COVID-19 lockdowns and she was left without work, with little to no social security.

Developing a Gender-Sensitive Jobs Plan


In this scenario, given the impact of COVID-19 on labour markets, governments, especially the central government can consider devising a short- to medium-term strategy for job-creation, which is gender-sensitive, and has clear targets for creation of women’s employment in both urban and rural areas. Some of the elements of such a gender-sensitive jobs plan include:

a. Incentivising Women’s Re-Hiring, Retraining, and Upskilling in the MSME Sector

States and the central government can work with small businesses to devise schemes which incentivise micro, small and medium enterprises (MSMEs) which hire a minimum proportion of women in the workforce. Incentives can also be provided for retraining and upskilling activities of their women employees.


b. Expanding support for women entrepreneurs

Out of 63.4 million MSMEs in India, only about 20% are women-owned, and remain concentrated in certain sectors like personal services (35%), apparel and textiles (31%) and food and other services (15%) (IFC, 2018). A July 2020 survey reported a 72.5% drop in their revenue, with 88% utilising personal savings to meet working capital needs (IWWAGE 2020).

These are small businesses witnessed a sharp demand shock with the onset of the nation-wide lockdown, and their revival has been slow. Even today, supply-chain constraints, mobility restrictions, and lack of market access has stymied the growth of these vibrant enterprises. There is a need to expand the National Rural Livelihood Mission to promote not only formation of SHGs, but to also assist women SHGs in scaling up to small enterprises and formalise, and pivot towards new businesses. Moreover, preferential procurement quotas for women-led enterprises for public sector contracts can also be reassessed and increased from the current 3%.

c. Expand job opportunities for women in public sector employment

State and central governments, and their agencies, are among the largest employers in the country. Vacancies in these institutions arise at several seniority and skill levels, including for semi-skilled persons as front-line construction contracts, for public works, as well as to operate public transport facilities. Women should be provided preference in filling these jobs and vacancies.

d. Create a pipeline of skilled women

Under the flagship Prime Minister Kaushal Vikas Yojana (PMKVY) for short-term skilling, although about half of the enrolled candidates over 2016-2020 were women, they remained concentrated in traditional, “feminised” sectors such as beauty, apparel, and healthcare. Women’s representation in longer-term skill training is much lower, and they formed only 17% of the enrolment at Industrial Training Institutes between 2014 to 2019 (MSDE and EY 2019). Therefore, moving forward, the Government of India could incentivise skill training institutes to increase women’s representation across trades, and create gender-sensitive infrastructure at skilling institutes.

E. Increase compensation of ASHA and Anganwadi workers

Over the last year, almost 2.5 million Anganwadi workers (AWWs), auxiliary nurse-midwives (ANMs) and accredited social-health activists (ASHAs) have walked, swum, and trudged across the length and breadth of the country, risking infection, and working over-time as the country’s front-line respondents during COVID-19.

This predominantly female group of ASHAs and AWWs are considered part-time volunteers and are not entitled to a fixed monthly wage from the central or state government. Therefore, in line with the recommendations of the Parliamentary Standing Committee on Labour (2020), ASHAs and AWWs should be recognised as employees, not volunteers, making them eligible for fixed monthly income and social security benefits. Their base salaries also need to be increased by state-level committees.


Gender is an important metric influencing availability of work, ability to make professional decisions, wages earned and long-term career growth. An analysis of data over the last seven decades shows that women’s work is largely informal, invisible, and labour-intensive. The COVID-19 pandemic has resulted in massive job losses for women and slower recovery of women-led microbusinesses. Over and above this, it has also increased unpaid domestic work, deepened gender digital divides, exacerbated gender-based skill and educational gaps and placed millions of women health workers at risk. In such a scenario, governments can respond by making a gender-sensitive employment creation plan a central plank of their economic recovery strategy.

The author would like to thank Vidhi Narang, Poorva Prabhu, Manvika Gupta, Ashruth Talwar, Mahak Mittal, Shruti Jha, Priyal Mundhra, Ashmita Chowdhury, and Shrushti Singh for their research and writing assistance.

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