‘What doesn’t get measured doesn’t get seen’. I’ve heard this phrase so many times but never has it felt truer than when it comes to unpaid care and domestic work.
Unpaid care and domestic work is the vital work that keeps our societies and economies ticking, keeping us healthy, nourished and nurtured and keeping our homes clean and tidy. But despite its importance, unpaid care work remains largely invisible. It is excluded from GDP and overlooked by governments and businesses in their policies and budgets. Across the world, unpaid care work is overwhelmingly provided by women. For centuries it has been considered women’s responsibility and not ‘work’.
All this probably explains why, as of 2018, only 16 countries had national time-use data on unpaid care work by women and men. This lack of data contributes to the continued invisibiliation of unpaid care work and the undervaluing of women’s labour. It makes it difficult to advocate for governments to recognise the value of unpaid care work and invest in care services and infrastructure.
Measuring unpaid care work with the Household Care Survey
In light of these data gaps, Oxfam developed the Household Care Survey (HCS) in 2015 through the WE-Care initiative. Today, we are launching a new toolkit to make the methodology widely available.
The HCS is a rigorous quantitative methodology to understand how women, men and children spend their time, how care is provided, by who, and the main factors that affect people’s unpaid care work responsibilities.
With findings from the HCS in rural Uganda and urban informal settlements of Kenya, we’ve been able to show that access to a water source reduces women’s time on care by between 1-4 hours a day. This is compelling evidence that civil society organisations have used to advocate with national and local governments on where and what to spend public money on.
An inspiring example of this is in the Philippines, where findings from the HCS were used to influence eight local governments who then passed Women’s Economic Empowerment and Care Ordinances (‘WEE-Care Ordinances’). These laws make it mandatory to generate data and address unpaid care in all local planning and budgeting. It’s unlikely such an outcome would have been possible without first having the convincing data on the extent of unpaid care work and how it affected women and girls’ lives.
What makes the Household Care Survey unique?
The HCS methodology follows international standards on time-use surveys, but it goes further. It looks at time-use in relation to context-specific factors such as access to:
- Care services (e.g. childcare and health care).
- Infrastructure (e.g. water, electricity and public transport).
- Time- and labour-saving equipment (e.g. washing machines and fuel-efficient stoves).
- Government social welfare schemes.
- Social norms, including perceptions of the value of care and acceptability of gender-based violence.
The HCS builds on the thinking of influential feminist economists such as Nancy Folbre, Valeria Esquivel, Shahra Razavi, Maria Floro and Naila Kabeer, and has several innovative components. This includes secondary and supervisory care hours, which are often not counted and therefore underestimated. Measuring supervisory care highlights the true extent of unpaid care work in women and girls’ lives.
Other survey components such as perceptions on social norms and the value of unpaid care work, children’s care hours, women’s health and wellbeing, and intersectional demographics such as age, poverty, religion and caste, provide a holistic picture of unpaid care work.
Using the Household Care Survey Toolkit
The HCS generates context-specific evidence and can be used to provide a baseline, or to measure changes over time and evaluate the impact of a specific policy or project.
While the methodology was first developed for use in low-income countries and rural communities, it can be easily adjusted to other contexts. The new toolkit provides core and optional questions to help do this. Some of the optional modules we have included are around high-income contexts, climate change, and COVID-19.
The toolkit is in two sections: Part A explains how to plan and implement the survey and use the findings, and Part B explains how to understand and adapt the survey questions. It is designed to be used by development practitioners, policymakers, academics and researchers alike. We’ve even added some helpful colour-coding to navigate the different sections based on what’s most important for you – whether it’s how to plan for data collection, develop a list of analysis variables, adapt the questions, or how to use the results for advocacy.
Check out the full toolkit here and let us know how you go in making unpaid care work counted and seen.
Author
