International Standards for Measuring Women’s Work: A Step Toward Equality

Every morning, millions of women across the country wake up to a long list of tasks: cooking meals, cleaning the house, fetching water, caring for children, helping the elderly, and managing the household. None of this work shows up in the national GDP. For decades, economists treated such labour as invisible because it did not pass through markets or generate wages. International statistical bodies have now developed frameworks to make this hidden work visible, count it accurately, and use it to shape better policies. Understanding these standards is essential to grasp how the global community is slowly redefining what counts as “work.”

Why measuring women’s work became a global concern
The SNA framework and the production boundary
The 2025 update to the SNA
Satellite accounts: a parallel ledger for invisible work
How satellite accounts value the work
Why childcare and elder care are tricky to measure
Time use surveys: the data backbone
What the Indian data revealed
From data to policy
The bigger picture: redefining progress

Why measuring women’s work became a global concern

Until the mid-twentieth century, official economic statistics largely ignored the labour performed inside households. When the United Nations System of National Accounts was first established in the late 1950s, its purpose was to create comparable data on productive activity across countries so that governments could plan policy and measure progress through indicators like Gross National Product. Unpaid care work, disproportionately performed by women, was deliberately left out of this framework, a decision that has been challenged ever since.

This omission created a serious gender bias in economic data. Unpaid domestic labour remained invisible to standard accounting even though it imposed a substantial time burden on women and effectively subsidised households, markets, and governments. Without numbers, there was no policy attention. Without policy attention, the inequality continued. International standards for measurement emerged as a response to this gap.

The SNA framework and the production boundary

The System of National Accounts is the global rulebook for compiling national economic statistics. It defines what counts as “production” through a concept called the production boundary. Activities inside the boundary are added to GDP; activities outside it are not. Unpaid work is split into two categories: work that falls within the SNA production boundary (such as subsistence farming, fetching water, or collecting firewood for the family’s use) and work that falls outside it (such as cooking, cleaning, childcare, and elder care performed for the household).

This distinction matters enormously. A woman who collects firewood for her family is, on paper, contributing to GDP. The same woman, when she returns home to cook with that firewood, is suddenly “unproductive” in statistical terms. Recognising this absurdity, the SNA has gradually expanded its treatment of unpaid work.

The 2025 update to the SNA

A significant shift came with the recent revision of the global framework. Through the 2025 updates, the SNA now encourages satellite accounts on unpaid work, allowing countries to measure and report unpaid household services without changing the core production boundary. This was a deliberate compromise: keep GDP comparable across countries, but build parallel accounts that finally make the invisible visible.

The revised framework, known as SNA 2025, integrates concerns of inequality, environment, and unpaid work into national accounts. It treats natural resources as assets, presents distributional accounts that show inequality between household groups, and explicitly includes household and care work in extended accounts. The goal is to move beyond GDP as the sole measure of progress.

Satellite accounts: a parallel ledger for invisible work

A satellite account is a supplementary set of national accounts that sits alongside the core SNA. It uses consistent definitions and methods but covers areas the main accounts ignore. For unpaid household work, this means estimating the value of cooking, cleaning, childcare, elder care, voluntary work, and other non-market services.

The conceptual foundation comes from economist Margaret Reid, who in 1934 proposed the “third party criterion”: if an activity could be delegated to a paid third person without losing its value to the household, it should be counted as production. Cooking a family meal passes this test because a cook could be hired. Sleeping or studying does not pass it because no one else can do those things for you.

How satellite accounts value the work

There are two broad methods. The first is the input approach, which uses time-use data to measure hours spent on each activity and then values those hours using a wage rate. The wage chosen could be the average economy-wide wage, the wage of a housekeeper, or the wage of a specialist (a cook for cooking time, a nurse for care time). The second is the output approach, which measures what households actually produce, such as meals prepared or children cared for, and values those outputs at market prices.

The United Kingdom’s Office for National Statistics has been a leader in this area. Its Household Satellite Account covers housing services, nutrition, transport, clothing and laundry, childcare, adult care, and volunteering. The estimates are striking. In earlier UK assessments, the value of home production was found to be larger than several major sectors of the formal economy combined, demonstrating just how much economic activity sits outside conventional GDP.

Why childcare and elder care are tricky to measure

Care work poses unique measurement challenges. Cooking has a clear start and end. Childcare often does not. A parent might cook dinner while keeping an eye on a toddler, then help with homework while folding laundry. Statisticians distinguish between active care (feeding, bathing, teaching), passive care (being on call while a child sleeps), and simply being in the same space as a dependent. As one Eurostat methodological paper notes, results from time-use surveys depend heavily on how primary, secondary, and supervisory care are classified. Decisions about what to include change the final value dramatically.

Elder care faces similar issues, especially in countries where ageing populations are growing and family members shoulder most of the responsibility. Properly measuring it requires capturing not just the hours spent on direct tasks but also the constant availability that caregivers must provide.

Time use surveys: the data backbone

Satellite accounts cannot exist without raw data on how people actually spend their time. This is where time use surveys come in. They ask respondents to record their activities in a 24-hour diary, typically in slots of 30 minutes or an hour, distinguishing between primary and secondary activities.

India’s first full-scale national time use survey was conducted by the National Statistical Office between January and December 2019, covering 1,38,799 households across rural and urban areas. The survey measured the participation rate and time spent on paid work, unpaid domestic services, care activities, learning, socialising, and self-care. It was a milestone because earlier rounds had been limited pilots in selected states.

What the Indian data revealed

The findings exposed a steep gender gap. An analysis of the 2019 Time Use Survey found that women spend roughly eight times more hours on unpaid care work than men. Women aged 15 to 59 in urban areas spent about 47 percent of their waking hours on unpaid care work, while in rural areas the figure was 43 percent. For men, the share was around 5 percent. The pattern held across educational qualifications and employment status, suggesting that gender norms, not economic logic, govern how household work is divided.

In urban areas, the gap between women’s and men’s unpaid work time was nearly three and a half times. The data also revealed that 94 percent of women engage in unpaid activities daily, compared to only about one-fifth of men. These numbers gave policymakers, for the first time, a clear empirical basis for talking about time poverty, the chronic shortage of time that reduces a person’s ability to rest, learn, earn, or participate in public life.

From data to policy

Time use data does more than describe the problem. It points to concrete interventions. If women in a region spend hours every day fetching water, investment in piped water supply directly reduces their unpaid workload and frees time for education or paid work. If childcare consumes large blocks of women’s time, public crèches and anganwadi expansions become economic policy, not just social welfare. If elder care burdens are rising, public health infrastructure and pension support reduce the squeeze on family caregivers.

This is why time use surveys are now treated as essential infrastructure for gender-responsive policy. They translate the lived reality of unpaid work into numbers that finance ministries and planning commissions can actually use. India is well-placed to adapt to SNA 2025 because of its groundwork in social surveys and time-use statistics, and regular updates to these surveys are now part of the official statistical agenda.

The bigger picture: redefining progress

International standards for measuring women’s work are part of a wider movement to look beyond GDP. The 2009 Stiglitz-Sen-Fitoussi Commission on the Measurement of Economic Performance and Social Progress argued that conventional indicators had drifted far from how ordinary people experienced their lives. Recognising unpaid work was central to closing that gap.

The shift is slow but real. Satellite accounts now exist in many advanced economies. Time use surveys have spread across developing countries. The SNA itself has been revised to make space for non-market household services. Together, these tools are building a more honest picture of what economies actually produce and who actually produces it. For women, who carry the largest share of the world’s unpaid labour, this measurement revolution is a quiet but powerful step toward equality.

What do you think? If India began publishing a full household satellite account alongside its GDP, how do you think public conversation about women’s work and economic policy would change? And which unpaid activity in your own household, if it were priced at a market wage, would shift your family’s understanding of who contributes the most?

References

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International Standards for Measuring Women’s Work: A Step Toward Equality

Table of Contents

Why measuring women’s work became a global concern 🔗

The SNA framework and the production boundary 🔗

The 2025 update to the SNA 🔗

Satellite accounts: a parallel ledger for invisible work 🔗

How satellite accounts value the work 🔗

Why childcare and elder care are tricky to measure 🔗

Time use surveys: the data backbone 🔗

What the Indian data revealed 🔗

From data to policy 🔗

The bigger picture: redefining progress 🔗