When we talk about economic growth, we rely on numbers. Gross Domestic Product tells us how much a country produces, how much it earns, and whether it’s progressing. But these numbers have a blind spot that affects billions of people, particularly women. The way we measure work systematically excludes unpaid labor, rendering invisible the hours spent cooking, cleaning, caring for children, and maintaining households. This isn’t just a statistical oversight-it shapes policies, influences perceptions of value, and perpetuates gender inequality.
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How we started counting work
The story of modern economic measurement begins in the 1940s. British economists James Meade and Richard Stone developed what would become the global standard for calculating GDP. Their focus was straightforward: measure the value of goods and services that were bought and sold in markets. This seemed logical for tracking wartime production and post-war recovery.
But there was a problem, and it came from an unexpected source. In 1941, Meade and Stone hired a 23-year-old woman named Phyllis Deane to apply their methods in British colonies. Working in present-day Malawi and Zambia, Deane realized something crucial: excluding unpaid household labor from GDP was a fundamental error. In rural Africa, women spent hours collecting firewood, fetching water, preparing food, and grinding corn. These activities were essential to survival and economic functioning, yet the accounting system ignored them entirely.
Deane argued that this exclusion was illogical and rooted in gender bias. She believed these tasks were left out precisely because they were viewed as women’s work. She conducted village surveys to measure burdensome activities and recommended including them in GDP calculations. If governments wanted accurate economic data and equitable policies, she insisted, they needed to count all producers-including rural women.
Her recommendations were ignored. In 1953, Richard Stone oversaw the publication of the United Nations’ first System of National Accounts, which set detailed standards for calculating GDP worldwide. The system excluded unpaid household labor, and because UN programs encouraged low and middle-income countries to follow these standards, the omission had global consequences.
Understanding the production boundary
At the heart of this exclusion is a concept called the production boundary. This is the imaginary line that separates activities considered economic production from everything else. Within this boundary falls work that is paid, sold, or intended for sale. Outside it falls most unpaid household services.
The System of National Accounts defines this boundary carefully. It includes goods and services supplied to others, production of goods for own consumption like backyard farming, and housing services provided by owner-occupiers. But it excludes most domestic services produced and consumed within households-cleaning, cooking, washing, meal preparation, and care for children and elderly family members.
Why draw the line here? The rationale is partly practical. National accounts are designed to help governments make market-based policy decisions. Household services are seen as isolated from markets and difficult to value meaningfully. But this technical justification has profound consequences.
What gets counted, what doesn’t
The production boundary creates strange contradictions. If you hire someone to clean your house, that transaction counts toward GDP. If you clean your own house, it doesn’t. If you buy prepared meals from a restaurant, GDP goes up. If you cook the same meals at home, GDP stays flat. The boundary doesn’t distinguish between productive and unproductive activities-it distinguishes between paid and unpaid ones.
This matters enormously for how we understand economies. Research from the US Department of Commerce found that incorporating household production would have raised GDP by 26 percent in 2010. That’s not a small adjustment-it’s a fundamentally different picture of economic activity.
The gendered reality of unpaid work
The exclusion of unpaid work isn’t gender-neutral. Women perform the vast majority of this labor. In OECD countries, women do about twice as much unpaid work as men-an average of 150 minutes more each day. Globally, more than 16 billion hours are devoted to unpaid domestic and care work every day.
The numbers are staggering. Nearly two-thirds of women’s weekly working hours do not enter GDP estimates because they don’t enter the market. In many countries, women spend more total time working when you combine paid and unpaid labor, yet their economic contribution appears smaller in official statistics.
This invisibility has real consequences. When unpaid care work doesn’t count in economic measurements, it’s easier to devalue it. Policies that cut public services force women to compensate with increased unpaid labor, but this doesn’t register as an economic loss. When care services are excluded from measures of economic productivity and well-being, it contributes to low societal value placed on both unpaid and paid care work.
Efforts to include unpaid work in the SNA
The System of National Accounts hasn’t remained static. In 2008, authors of the updated SNA responded to decades of criticism with a compromise. They agreed to include production of all goods-whether sold or not-in GDP calculations. Activities like weaving mats or brewing beer would now count. But they continued to exclude most unpaid household services like cooking and cleaning.
More recently, momentum has been building. The System of National Accounts 2025 marks a significant shift. It moves beyond GDP-centric measurement to integrate concerns about inequality, environment, and unpaid work. The new framework includes extended accounts that recognize household and care work, explicitly acknowledging women’s contributions.
The framework recommends measuring unpaid household service work in both physical units and monetary values, keeping these measures as consistent as possible with the core system while making them relevant to monitoring household economic well-being. This means countries can produce supplementary tables showing the value of unpaid work alongside traditional GDP figures.
How unpaid work would be measured
Measuring unpaid work requires different tools than measuring market transactions. The primary method is time-use surveys. These track how people spend their days-how many hours go to paid work, unpaid work, and leisure. In 2013, the International Conference of Labour Statisticians formalized definitions to distinguish work from other activities, using the principle that work produces goods or services for use by others or for own use.
Once time is measured, it needs to be valued. Several approaches exist. One method assigns market wages for equivalent services-what would it cost to hire someone to do this work? Another approach values time based on opportunity cost-what could the person have earned doing paid work instead? Conservative estimates suggest unpaid domestic and care work would equal over 40 percent of GDP in some countries.
Why inclusive measurement matters
Counting unpaid work isn’t just about fairness-it’s about accuracy. Economic policies based on incomplete data produce incomplete solutions. When GDP treats oil spills and military spending as positive contributions but deems care for children valueless, it distorts our understanding of progress and well-being.
Consider public policy decisions. Governments allocate resources based on economic data. If care work is invisible in statistics, investments in care infrastructure seem economically unproductive. If women’s time appears infinite and free, there’s no urgency to provide public childcare, elder care services, or basic infrastructure like clean water access. Yet hundreds of millions of women worldwide walk more than 30 minutes round-trip to reach clean water for their families-time that could be spent on education, paid employment, or rest.
More accurate measurement can reveal economic potential. Studies show that increasing women’s labor force participation can have substantial positive impacts on GDP. When a significant portion of the population cannot fully engage in the labor market because of unpaid care responsibilities, the economy operates below potential. Understanding this requires measuring both paid and unpaid work.
Beyond GDP as the sole metric
The limitations of GDP have sparked interest in alternative measures of well-being. A 2009 report commissioned by French President Nicolas Sarkozy found that treating GDP as a measure of economic well-being can lead to misleading indicators and wrong policy decisions. Alternative frameworks emphasize care and capabilities, culture and leisure, connections with nature and community, and democratic participation.
Some countries have started producing this data. Time-use surveys provide evidence that can integrate invisible labor into policy planning. India’s 2019 Time Use Survey, for instance, found women spent 134 minutes per day on unpaid caregiving work compared to 76 minutes for men, and 200 minutes more on domestic work. This data makes inequality visible and measurable.
The goal isn’t to replace GDP but to complement it. Extended accounts can sit alongside core national accounts, providing a fuller picture without disrupting established measurement systems. This allows policymakers to see both market production and the unpaid work that makes market production possible.
Moving toward better standards
The path forward requires continued pressure and methodological innovation. International guidance has evolved since 2008, with updated standards for measuring unpaid household service work. The challenge now is implementation-ensuring countries collect the necessary data and integrate it into policy analysis.
Technology can help. Time-use surveys can be attached to labor force surveys, making data collection more efficient. Digital tools can reduce the burden of tracking activities. As more countries produce this data regularly, comparability improves and best practices emerge.
But measurement alone won’t eliminate gender inequality. It’s a necessary step, not a sufficient one. Making unpaid work visible in statistics must be accompanied by policies that redistribute it more equitably and provide public support for care work. The goal is not just to count women’s invisible labor but to create conditions where care responsibilities are shared and supported.
What do you think? How might your understanding of economic progress change if care work and household labor were consistently included in official statistics? What policies might shift if governments based decisions on data that included both paid and unpaid contributions to well-being?
References
- https://www.weforum.org/stories/2018/06/women-s-unpaid-work-must-be-included-in-gdp-calculations-lessons-from-history/
- https://www.unescwa.org/sd-glossary/production-boundary
- https://unstats.un.org/unsd/nationalaccount/sna.asp
- https://www.abs.gov.au/statistics/detailed-methodology-information/concepts-sources-methods/australian-system-national-accounts-concepts-sources-and-methods/2020-21/chapter-8-gross-domestic-product/production-boundary
- https://en.wikipedia.org/wiki/Unpaid_work
- https://www.weforum.org/stories/2016/04/why-economic-policy-overlooks-women/
- https://ilostat.ilo.org/topics/unpaid-work/measuring-unpaid-domestic-and-care-work/
- https://views-voices.oxfam.org.uk/2023/08/a-flawed-gdp-bypasses-womens-unpaid-care-work/
- https://iwpr.org/wp-content/uploads/2020/01/IWPR-Providing-Unpaid-Household-and-Care-Work-in-the-United-States-Uncovering-Inequality.pdf
- https://www.insightsonindia.com/2025/08/29/system-of-national-accounts-2025/
- https://unstats.un.org/unsd//nationalaccount/aeg/2020/M14_6_7_Unpaid_HH_Service_Work.pdf
- https://unstats.un.org/UNSD/nationalaccount/RAdocs/WS3_Unpaid_HH_Service_Work_Paper.pdf
- https://www.economy.com/getfile?q=12205E68-6FDC-4C35-979C-EDEF18CE149F&app=download
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