Redefining Women’s Work: Recognizing Hidden Contributions

When we hear the word “work”, we usually think of a salaried job, a shop, a factory, or a farm where someone gets paid. But what about the woman who wakes up at 5 am to fetch water, cook for the family, milk the cow, tend to the kitchen garden, and look after children and elders, all without a single rupee in return? For decades, statisticians and economists have struggled with a basic question: does this count as “work”? The way India answers this question has huge consequences, because how we define women’s work directly decides whether millions of women are visible in our economy or invisible.

Why the conventional definition leaves women out 🔗

The traditional definition of “work” in economic statistics is borrowed from the United Nations System of National Accounts (SNA). Under this framework, an activity is considered “economic” only if it produces goods or services for the market, i.e., something that is bought, sold or exchanged for money. Wages, salaries, and self-employment income fit neatly here. Cooking for your own family, however, does not, even though the same activity, done in a restaurant or in someone else’s home, would suddenly become “work”.

This narrow boundary creates a strange paradox. A woman who cooks meals at a roadside dhaba is counted as a worker. The woman who cooks the exact same meals for her husband, children, and in-laws at home is counted as a “homemaker” and pushed out of the labour force entirely. The result is a sharply skewed picture of who contributes to the economy.

The scale of the invisibility 🔗

The numbers are striking. According to analysis of the National Statistical Office’s Time Use Survey 2019, more than 92 percent of women aged 15-59 years participated in unpaid domestic services for their households, against just 29 percent of men. Yet under conventional labour force definitions, almost none of this activity is counted as work. Pioneering feminist economist Devaki Jain, who spent decades pushing the NSSO to reform its methods, has long argued that to properly capture women’s contribution, the very idea of work itself needs to be rethought, with time-use as a more honest measure than market exchange.

Conventional definitions of women’s work 🔗

Indian official statistics historically relied on two big sources: the decennial Population Census and the rounds of the National Sample Survey Organisation (NSSO), now reorganised under the National Statistical Office. Both used the concept of “usual principal activity status” or “usual principal and subsidiary status” to classify a person as a worker.

Under this system, individuals are bucketed into codes. Activity codes 11-51 cover “workers” (self-employed, wage earners, casual workers, etc.). But two codes have been the centre of long-standing debate: code 92 and code 93. Code 92 covers women “attending to domestic duties only”, while code 93 covers women “attending to domestic duties and also engaged in free collection of goods, sewing, tailoring, weaving, etc., for household use.” According to UN Women’s analysis, even women whose activities fall within the SNA production boundary often get placed in code 93 and are denied official recognition as workers.

The “principal activity” trap 🔗

Another problem is the way the principal activity is decided. Investigators typically ask what a person did for the “major part of the year”. Since women combine many short-duration tasks, including paid work, family-farm labour, livestock care, and household chores, they frequently get classified by their most visible role: housewife. A woman who spends three hours daily milking buffaloes, four hours weeding a family field, and another six hours cooking and cleaning is often recorded simply as “engaged in domestic duties”. The same researcher analysing a man with similarly mixed activities will typically classify him as a “cultivator” or “farm worker”.

Studies have shown that this introduces a strong downward bias in female labour force participation. The ILO’s research on India’s declining female LFPR notes that because women are disproportionately engaged in unpaid domestic and care work, conventional measurement instruments are particularly likely to misclassify them.

Broader definitions through the NSSO and Census 🔗

Pressure from feminist economists, beginning with the 1982 Time Allocation Survey by Devaki Jain and Malini Chand in West Bengal and Rajasthan, led to gradual changes. The NSSO began asking supplementary questions to identify women within codes 92 and 93 who were also engaged in activities that, by SNA standards, should count as work.

These activities include:

Free collection of goods: firewood, cattle feed, edible roots, fruits, water, fish for household consumption. Anyone who has visited a rural area knows that fetching water from a distant handpump or collecting firewood from a forest is heavy, time-consuming labour. Under a strict interpretation of the SNA, the collection of items for household use that would otherwise have to be purchased is genuinely productive activity.

Poultry, dairy and livestock care: rearing chickens, milking cows, feeding goats, even when produce is partly consumed at home. A 2025 primary study from Bihar documented that upper- and middle-caste women spent around three hours a day on household dairying, producing milk that was sold in the market and yet remained statistically invisible because the work happened within the household periphery.

Kitchen gardens: growing vegetables and fruits in backyards for household consumption.

Sewing, tailoring, weaving, husking, and food processing done at home for the family.

When women in code 92/93 who reported these “additional” activities were reclassified as workers, the female workforce participation rate rose substantially. The NSSO began publishing both narrower and broader estimates, allowing scholars to see how dramatically definitions matter.

The Time Use Survey breakthrough 🔗

A landmark shift came with India’s first nationwide Time Use Survey (TUS) in 2019, conducted by the National Statistical Office. Unlike conventional surveys that ask about “principal activity”, the TUS asks respondents what they did in each 30-minute slot over a 24-hour period. This methodology, which Devaki Jain had championed since the 1980s, captures the continuum of women’s work far better than a one-line question ever could.

The findings were powerful. According to Time Use in India-2019, women spent an average of 299 minutes per day on unpaid domestic services compared to just 97 minutes for men. In urban areas, women spent 82.9 percent of their total work time on unpaid activities, while men spent 87.9 percent of their time on paid activities – almost mirror opposites.

The second TUS, conducted in 2024, showed only marginal change. The Wire’s analysis noted that fewer women participated in employment-related activities than men, but a much larger share of women participated in unpaid domestic work and caregiving services, with the gendered pattern essentially unchanged in five years.

Micro-level studies and what they reveal 🔗

Large-scale surveys, even improved ones, can only do so much. Micro-level studies, often based on a few villages or districts, have been crucial in exposing exactly how invisibility works on the ground.

Caste, class, and the household periphery 🔗

The Bihar study mentioned earlier is illustrative. Researchers found that caste and class shape what gets counted. Lower-caste women typically go out to work in fields, brick kilns, or as agricultural labourers, and so their work is more visible to enumerators. Upper- and middle-caste women, constrained by purdah norms and household honour, perform substantial economic work – dairying, kitchen gardening, processing – but always within the household compound, where surveyors fail to see it. The result is that “women’s work participation” is undercounted especially for groups where socio-cultural norms confine work indoors.

The continuum of work 🔗

Micro studies also reveal that the line between “paid” and “unpaid” or “productive” and “domestic” is blurry. The same woman may, in a single day:

Cook a meal for her family (unpaid, not counted).
Pack lunch for her husband to take to the farm (unpaid, part of family enterprise).
Help in the family field for two hours (unpaid family labour, sometimes counted).
Sell surplus vegetables from the kitchen garden at the local market (paid, counted).
Stitch clothes for a neighbour for a small fee (paid, often missed by surveys).

Conventional surveys force this continuum into a single principal-activity box. Time-use methods, by contrast, let researchers see the full mosaic.

Reshaping our understanding of contribution 🔗

Once unpaid work is properly accounted for, the picture of who supports the Indian economy changes dramatically. Studies published in The India Forum have argued that India’s official female LFPR – one of the lowest in the world – is partly a statistical artefact. If we used the broader 19th International Conference of Labour Statisticians (ICLS) definitions, which separate “employment” from “own-use production work” but recognise both as forms of work, women’s participation would jump substantially.

Economists have attempted to value this hidden contribution. The Observer Research Foundation notes that Indian women perform roughly eight times more hours of unpaid care work than men, a contribution that, if monetised, would amount to several percentage points of GDP. This is the economic value the household, and by extension the nation, receives for free.

Why redefining women’s work matters 🔗

This is not just a debate about numbers. How we measure has real-world consequences. When women’s work is invisible:

Policy ignores them. Skill training, credit schemes, and social security programmes are designed for “workers”. Women classified as “housewives” are missed.

Wages stay depressed. If society sees domestic work as a “natural duty” rather than work, paid domestic workers, overwhelmingly women, are paid badly.

Gender budgeting is distorted. Without good data, governments cannot allocate resources to reduce women’s drudgery, build crèches, or improve water supply that would free up women’s time.

Empowerment narratives go wrong. A girl who is told “your mother does not work” internalises a powerful message about the worth of women’s contribution.

The “triple R” approach – recognise, reduce, redistribute – argues that the first step is recognition. Counting is itself a political act.

The road ahead 🔗

India’s statistical system has come a long way from the days when women’s work was casually equated with idleness. The Time Use Surveys of 2019 and 2024, the introduction of supplementary questions in NSSO rounds, and the rising use of micro studies have all enriched our picture. Yet much remains to be done. Investigators still need better training to probe beyond the easy “housewife” answer. The Periodic Labour Force Survey (PLFS) could integrate time-use insights more systematically. Above all, recognition needs to translate into redistribution: better child care, water and fuel infrastructure, and more equal sharing of housework within families.

Until then, every time we hear someone say “my mother does not work”, we should pause and ask: is that really true, or is it just that nobody bothered to count?

What do you think? If unpaid domestic and care work were assigned a monetary value and included in GDP, how would that change the way you view your own household? And do you think Indian families and workplaces are ready to redistribute domestic work between men and women, or is recognition alone going to remain the easy first step?

References

1. https://www.orfonline.org/research/building-india-s-economy-on-the-backs-of-women-s-unpaid-work-a-gendered-analysis-of-time-use-data
2. https://thethirdeyeportal.in/structure/time-could-be-the-only-measure-for-womens-labour/
3. https://asiapacific.unwomen.org/sites/default/files/Field%20Office%20ESEAsia/Docs/Publications/2019/04/in-Invisible-Work-and-Invisible-Workers-compressed.pdf
4. https://www.ilo.org/sites/default/files/wcmsp5/groups/public/@dgreports/@inst/documents/publication/wcms_250977.pdf
5. https://link.springer.com/article/10.1007/s41027-025-00555-3
6. https://ruralindiaonline.org/en/library/resource/time-use-in-india-2019/
7. https://m.thewire.in/article/gender/what-the-time-use-survey-says-about-womens-work
8. https://www.theindiaforum.in/article/reconceptualising-womens-work-national-sample-survey